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This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Read more

This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Practical machine learning skill development is at the core of this programme, which is specifically designed to maximise employment potential across a wide spectrum of industrial and academic posts related to AI.

AI is rapidly changing the way we live, work and learn. Both governments and industry have recognised the need for strategic development of AI -- technology giants such as Google, Microsoft and Facebook have each established their own AI research institutes, and the UK government recently announced its £75 million investment in the November 2017 Budget.

There is however a real shortage of AI talents worldwide, both to serve the industry and drive future research. AI jobs are amongst the best paid in industry nowadays – an AI Specialist typically earns among the highest salaries (New York Times, 22nd Oct 2017), while having a solid AI background is strongly desired in multiple research disciplines.

MSc Artificial Intelligence importantly recognises such need for training cutting-edge AI talents, and is specifically designed to maximise student employability on AI-specific jobs.

This programme is:

  • comprehensive: covering all five of the most popular AI topics
  • up-to-date: each topic backed up by a world-leading group with cutting edge research
  • unique: offering Game AI that represents some of the most advanced AI to date (e.g., AlphaGo)
  • practical: focusing on developing practical machine learning skills across all five AI topics.

The programme brings together our teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.

Industrial Experience

The industrial placement takes place from the September following the taught part of the MSc for a maximum of 12 months. It is a student's responsibility to secure their own placement, but the EECS Placement Team will provide support. The Placement Team source and promote suitable opportunities, assist with applications, and with interview preparation.

The industrial placement consists of 8-12 months spent working with an appropriate employer in a role that relates directly to your field of study. The placement is currently undertaken after you have completed, passed the taught component of the degree and submitted your MSc project. The placement will provide the opportunity to apply key technical knowledge and skills gained from your taught modules and will enable you to gain a better understanding of your own abilities, aptitudes, attitudes and employment potential. The module is only open to students enrolled on a programme of study with integrated placement.

In the event that you are unable to secure a placement, we will transfer you onto the 1 year FT taught programme without the Industrial Experience. This change will also apply to any student visa you hold at the time.

Structure

MSc Artificial Intelligence is currently available for one year full-time study or two years part-time study.

Full-time (The programme is organised in three semesters)

Semester 1: Four modules that operate on a 3+1 scheme

3 core modules that cover the foundational machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).

Semester 2: Four modules themed around all five AI topics offered

The module selection allows students to focus on topic-specific research or industry applications for AI. More importantly, these module options allow students to gain advanced and up-to-date knowledge on selected AI topics.

Semester 3:

Students carry out a large project on the AI topic that they want to specialise in, after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.

Undertaking a masters programme is a serious commitment, with weekly contact hours being in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.

Part-time

Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.

Core modules:

·       Computational Intelligence and Games

·       Machine Learning

·       Data Mining

·       MSc Project module

Option modules:

·       Introduction to Computer Vision

·       Machine Learning for Visual Data Analysis

·       Deep Learning and Computer Vision

·       Music Perception and Cognition

·       Music and Speech Modelling

·       Music Analysis and Synthesis

·       Natural Language Processing

·       Advanced Natural Language Processing

·       Artificial Intelligence

·       Information Retrieval

·       Advanced Robotics Systems

·       Multi-platform Game Development



*All new courses are required to undergo a two-stage internal review and approval process before being advertised to students. Courses that are marked "subject to approval" have successfully completed the first stage of this process. Applications are welcome but we will not make formal offers for this course until it has passed this second (and final) stage.



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This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Read more

This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Practical machine-learning skill development is at the core of this programme, which is specifically designed to maximise employment potential across a wide spectrum of industrial and academic posts related to AI.

Artificial Intelligence is rapidly changing the way we live, work and learn. Both governments and industries have recognised the need for strategic development of AI -- technology giants such as Google, Microsoft and Facebook have each established their own AI research institutes, and the UK government recently announced its £75 million investment in the November 2017 Budget.

There is however a real shortage of AI talents worldwide, both to serve the industry and drive future research. Artificial Intelligence jobs are amongst the best paid in industry nowadays – an AI Specialist typically earns among the highest salaries (New York Times, 22nd Oct 2017), while having a solid AI background is strongly desired in multiple research disciplines.

MSc Artificial Intelligence importantly recognises such need for training cutting-edge AI talents, and is specifically designed to maximise student employability on AI-specific jobs.

This programme is:

• comprehensive: covering all five of the most popular AI topics

• up-to-date: each topic backed up by a world-leading group with cutting edge research

 unique: offering Game AI that represents some of the most advanced AI to date (e.g., AlphaGo)

• practical: focusing on developing practical machine-learning skills across all five AI topics

The programme brings together our teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine-learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.

Structure

MSc Artificial Intelligence is currently available for one year full-time study or two years part-time study.

Full-time (programme organised into three semesters)

Semester 1: Four modules that operate on a 3+1 scheme

3 core modules that cover the foundational machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).

Semester 2: Four modules themed around all five AI topics offered

The module selection allows students to focus on topic-specific research or industry applications for AI. More importantly, these module options allow students to gain advanced and up-to-date knowledge on selected AI topics.

Semester 3:

Students carry out a large project on the AI topic that they want to specialise in, after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.

Undertaking a masters programme is a serious commitment, with weekly contact hours in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching, independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.

Part-time

Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.

Important note regarding Part Time Study

We regret that due to complex timetabling constraints, we are not able to guarantee that lectures and labs for part time students will be limited to two days per week, neither do we currently support any evening classes. If you have specific enquiries about the timetabling of part time courses, please contact the MSc Administrator

Core modules:

·       Computational Intelligence and Games

·       Machine Learning

·       Data Mining

·       MSc Project module

Option modules:

·       Introduction to Computer Vision

·       Machine Learning for Visual Data Analysis

·       Deep Learning and Computer Vision

·       Music Perception and Cognition

·       Music and Speech Modelling

·       Music Analysis and Synthesis

·       Natural Language Processing

·       Advanced Natural Language Processing

·       Artificial Intelligence

·       Information Retrieval

·       Advanced Robotics Systems

·       Multi-platform Game Development

*All new courses are required to undergo a two-stage internal review and approval process before being advertised to students. Courses that are marked "subject to approval" have successfully completed the first stage of this process. Applications are welcome but we will not make formal offers for this course until it has passed this second (and final) stage.



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Your programme of study. If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. Read more

Your programme of study

If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. You must have covered either computer science or electrical and electronic engineering as your first degree or a suitable combination to study this Master's degree. The digital age is changing the way we live, communicate, interact and our quality of life rapidly. Cloud based networks are now normal, autonomous vehicles are being explored, visual recognition, GIS aligning to our search interests, data mining to inform us automatically at any point in time what is happening around us and new methods to inform us of danger, awareness, alerts and so on.

Artificial Intelligence provides in depth knowledge of data mining, natural language, information visualisation and communication used in Industry 4.0 innovation industries such as autonomous vehicles, sensor data collection and computation, visual computer recognition software and machine to machine technologies. It is also said that artificial intelligence has the potential to change how we research and act to provide immediate solutions to energy, travel, and gridlock before it happens by setting up more alerts and warnings to us. We now already have the capabilities in smart technology to alert us on maps, apps, weather stations, lighting, sensors and other electronic and wired machine to machine devices to provide instant relevant information.

You are also advised to visit the organisation websites via the link below to find out about the innovations which may be influenced by AI:

Scottish Innovation Centres -

Courses listed for the programme

SEMESTER 1

Compulsory Courses

  • Foundations in AI
  • Machine Learning
  • Evaluation Systems of AI Systems
  • Engineering of AI Systems

SEMESTER 2

Compulsory Courses

  • Data Mining and Visualisation
  • Natural Language Generation
  • Software Agents and Multi-Agent Systems
  • Knowledge Representation and Reasoning

SEMESTER 3

You can broaden and deepen your skills with industry client opportunities where possible

Find out more detail by visiting the programme web page

Why study at Aberdeen?

  • AI or Artificial Intelligence is part of a major industrial revolution globally, linking to the Internet of Things
  • Aberdeen gives you a strong worldwide reputation for teaching in computing science, data science and natural language generation
  • You can be involved in cutting edge innovations which will shape our world in the future

Where you study

  • University of Aberdeen
  • 12 Months Full Time
  • September start

International Student Fees 2017/2018

Find out about fees:

*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.

Scholarships

View all funding options on our funding database via the programme page and the latest postgraduate opportunities

Living in Aberdeen

Find out more about:

Your Accommodation

Campus Facilities

Find out more about living in Aberdeen and living costs

You may also be interested in:

Information Technology MSc - Campus or Online



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Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans. Read more

Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.

The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.

On the one hand, the Master’s in Neural Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.

On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.

See the website http://www.ru.nl/english/education/masters/neural-computing/

Why study Neural Computing at Radboud University?

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- Together with the world-renowned Donders Institute, the Behavioural Science Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.

- Deep learning

Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.

-Computational framework for counterfactual predictive processing

In a recent paper we introduced a computational framework, based on causal Bayesian networks, to computationally flesh out the predictive processing processing framework in neuroscience. In this project we want to extend this to so-called counterfactually rich generative models in predictive processing. Such models encode sensorimotor contingencies, that is, they represent 'what-if' relations between actions and sensory inputs. We aim to further operationalize this account using Pearl's intervention and counterfactual semantics. In this project you will combine formal computational modelling with conceptual analysis. 

- Brain Computer Interfacing

Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight and technical expertise . A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies or joined recent startups.

Job positions

Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:

- PhD researcher on bio-inspired computing

- PhD researcher on neural decoding

- PhD researcher on neural information processing

- Machine learning expert in a software company

- Company founder for brain-based computer games

- Hospital-based designer of assistive technology for patients

- Policy advisor on new developments in neurotechnology

- Software developer for analysis and online visual displays of brain activity

Internship

Instead of an extended research project (45 ec) you can also choose to do a smaller (30 ec) research project plus a 15 ec internship, giving you plenty of hands-on experience with AI. We encourage students to do this internship abroad.



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Overview. Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems. Read more

Overview

Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems.

As humans, we may be intrigued by the complexity of any daily activity. How do we perceive, act, decide, and remember? On the one hand, if we understand how our own intelligence works, we can use this knowledge to make computers smarter. On the other hand, by making computers behave more like humans, we learn more about how our own cognition works.

The AI Master’s programme at Radboud University has a distinctly cognitive focus. This cognitive focus leads to a highly interdisciplinary programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

See the website http://www.ru.nl/masters/ai

Scientific and practical applications

Slowly the human brain has been revealing its mystery to the scientific community. Now that we are actually able to model and stimulate aspects of cognition, AI researchers have gained a deeper understanding of cognition. At the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres, we train our students to become excellent researchers in this area.

At Radboud University we also teach students how to develop practical applications that will become the next generation of products, apps, therapies and services. Our department has been awarded several prizes for its pioneering role in bringing innovations from science to society, e.g. in Assistive Technology for people with disabilities. You’ll be taught the skills needed to conduct and steer such innovation processes. Many Master’s research projects have both a scientific and a practical component.

Specialisations

Computational modelling is the central methodology taught and used in this programme. Depending on the area of study, the computational models can range from behavioural models of millions of individuals interacting on the web, to functional models of human or robot decision-making, to models of individual or networks of artificial neurons. At Radboud University we offer the following three specialisations (on campus simply known as Computation, Robot and Web):

- Neural Computing

Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.

- Interactive Agents

Developing intelligent machines and new ways for humans and machines to interact, as well as understanding cognition through human behavior.

Research project and Internship

To finalise your AI master's programme, you have the choice of either an Internship (18EC) and Research Project (30EC) or a single larger Extended Research Project (48EC). During the internship you have the chance to acquire additional AI relevant skills either at a research lab or at a company. During the Research Projects phase, you get to put what you have learned during your master's programme into practice. You can perform your research work in the AI department, at other research departments at the University (e.g. the Behaviour Science Institute or Donders Institute) or at an external company (such as Philips or TNO). You are also encouraged to go abroad for your internship and/or research project (previously students have gone to Stanford University in California and Aldebaran Robotics in Paris). To help you decide on a thesis topic, there is an annual Thesis Fair where academics and companies present possible project ideas.

Job opportunities

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or a university with an AI department. Other graduates have started their own companies or work for companies interested in cognitive design and research.

Find out how to apply here http://www.ru.nl/masters/ai

Meet Radboud University

- Information for international students

Radboud University would like to meet you in your country (http://www.ru.nl/meetus) in order to give all the information you need and to answer any questions you might have about studying in the Netherlands. In the next few months, an advisor of Radboud University will be attending fairs in various countries, always accompanied by a current or former student.

Furthermore, we understand if you would like to see the Radboud Campus and the city of Nijmegen, which is why we organise an Master's Open Day for international students, which you are welcome to attend (http://www.ru.nl/openday).

- Information for Dutch students

Radboud University offers students in the Netherlands plenty of opportunities to get more information on your programme of choice, or get answers to any questions you might have and more. Apart from a Master's Evening and a Master's Day, we also organise Orientation Days and a Master’s Afternoon for HBO students.



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The Need for Cybersecurity. Many of our societal infrastructures have been digital for quite some time, e.g. telecoms, banking, and e-commerce, and social media. Read more

The Need for Cybersecurity

Many of our societal infrastructures have been digital for quite some time, e.g. telecoms, banking, and e-commerce, and social media. The trend to increasing digitization continues apace, with areas such as health, power distribution, transport and manufacturing increasingly embracing the opportunities digitisation offers. In particular, the drive to increased automation and ‘smart’ operation inevitably means increased use computation.

The Internet of Things, perhaps the highest profile development in computing of recent times, marks a step change in connectivity, with some estimating 50 billion devices coming on-line by 2020. There is little doubt that we are hugely dependent on interconnected devices and systems and there are many opportunities to inflict malicious damage on them. Unsurprisingly, cybersecurity problems are reported in the media everyday. Cybersecurity is one of the most pressing problems of our day and securing computational systems and infrastructures is critical for healthy operation of modern societies.

Why Cybersecurity and Artificial Intelligence?


Artificial Intelligence (AI) has achieved an exceptional profile in recent years. If cybersecurity is one of the most pressing problems of our day then AI is perhaps the highest profile solution technology. Much ’smart’ infrastructure is underpinned by AI and the provision of insight via data analytics is becoming pervasive. Harnessing AI to provide more secure component and system designs and to provide insights into system operation, e.g. to detect intruders, is a natural goal.

AI underpins so much of the operation of modern day smart infrastructural and the AI algorithms and systems at the heart of such operation may themselves be maliciously attacked with great effect, e.g. the insertion of trapdoors into the neural networks that provide image recognition for automated car operation could cause catastrophic loss of life. Additionally, smart ‘attacks’ supported by AI means are now beginning to emerge; this introduces a new and worrying level of sophistication.

There is little doubt that AI will play a variety of offensive and defensive roles in the area of cybersecurity. Our MSc programme provides a grounding in cybersecurity fundamentals. It also provides a grounding in aspects of AI of significant relevance to cybersecurity, covering fundamental and widely applicable machine learning technologies, the computational support to use them, and specific data analytics technologies (text and speech processing).

Why Cybersecurtiy and Artificial Intelligence at Sheffield?

  • Be in demand - our course has been developed to meet acknowledged skills gaps.
  • Gain the specific skills increasingly valued by employers. Our programme has been developed with significant support from employers (who will also deliver the programme).
  • Access to a dedicated employability team to help increase your employment prospects.
  • Teaching informed by researchers working in relevant areas such as Cybersecurity, Machine Learning, Text and Natural Language Processing.
  • The Department of Computer Science is 5th in the UK for Research Excellence (REF 2014).


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Get paid to do a Masters with the. Centre for Global Eco-Innovation. at. Lancaster University. , The Sunday Times University of the Year 2018, and. Read more

Get paid to do a Masters with the Centre for Global Eco-Innovation at Lancaster University, The Sunday Times University of the Year 2018, and Invisible Systems.

One year enterprise-led funded Masters by Research, Ref. No. 104

·        Get paid £15,000 tax-free

·        Have your tuition fees reduced. Your partner company pays £2,000 towards your fees, meaning UK/EU students pay £2,260, and international students pay £15,945.

·        Be part of the multi award winning Centre for Global Eco-Innovation with a cohort of 50 talented graduates working on exciting business-led R&D.

·        The Centre is based at Lancaster University, so you will gain your Masters from a Top Ten University, recognised as The Sunday Times University of the Year 2018.

·        Finish in a strong position to enter a competitive job market in the UK and overseas.

Commercial properties consume significant amounts of energy on heating and depend on relatively simple control systems. More advanced Smart Heating controls are now available for residential homes but are less common in commercial properties. The aim of this project is the development of a new boiler control system for commercial properties, with the aim of reducing energy consumption, carbon footprint and ongoing running costs.

This project will involve research and development to understand the range of technologies currently available, model system behaviours and develop control algorithms to implement the outcomes of research. It will also aim to discover new possibilities resulting from the inter-connection of IoT technologies, develop these into a commercial product and explore new approaches for complex systems with a focus on AI and machine learning.

This project would suit applicants with an engineering degree and programming experience, or a computer science graduate with a scientific leaning.

Enterprise and collaborative partners

This Masters by Research is a collaborative research project between Lancaster University, with supervision from Dr Peter Garraghan and Invisible Systems. Invisible Systems is a software and electronics design manufacturing company that focuses on energy saving, compliance and asset management via robust RF wireless monitoring and energy savings solutions with our realtime-online cloud software management portal.

Apply Here

To apply for this opportunity please email with:

·    A CV (2 pages maximum)

·    Application Form

·    Application Criteria Document

·    Reference Form

This project is part funded by the European Regional Development Fund and is subject to confirmation of funding. For further information about the Centre for Global Eco-Innovation, please see our website.

 

Deadline:           Midnight Wednesday 18th July 2018

Start:                    October 2018



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Understanding all aspects of Human-Robot interaction. the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot. Read more

Understanding all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.

At present, there are many sensors and actuators in every device – so they may become embedded in a physical reality. For robots that move around in a specific setting there is a pressing need for the development of proper methods of control and joint-action. The embedded, embodied nature of human cognition is an inspiration for this, and vice versa. Computational modelling of such tasks can give insight into the nature of human mental processing. In the Master’s specialisation in Robot Cognition you’ll learn all about the sensors, actuators and the computational modelling that connects them.

Making sense of sensor data – developing artificial perception – is no trivial task. The perception, recognition and even appreciation of sound stimuli for speech and music (i.e. auditory scene analysis) require modelling and representation at many levels and the same holds for visual object recognition and computer vision. In this area, vocal and facial expression recognition (recognition of emotion from voices and faces) is a rapidly growing application area. In the area of action and motor planning, sensorimotor integration and action, there are strong links with research at the world-renowned Donders Centre for Cognition.

At Radboud University we also look beyond the technical side of creating robots that can move, talk and interpret emotions as humans do. We believe that a robot needs to do more than simply function to its best ability. A robot that humans distrust will fail even if it is well programmed. Culture also plays a role in this; people in Japan are more open to the possibilities of robots than in, for example, the Netherlands. We will teach you how to evaluate humans’ attitudes towards a robot in order to use that information to create robots that will be accepted and trusted and therefore perform even better.

See the website http://www.ru.nl/masters/ai/robot

Why study Robot Cognition at Radboud University?

- We offer a great mix of technical and social aspects of robot cognition.

- This programme focuses on programming robot behaviours and evaluating them rather than building the robots themselves. We teach you to programme robots that will be used in close contact with human beings, for example in healthcare and education, rather than in industry.

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You could also cooperate with the Behavioural Science Institute and work in its Virtual Reality Laboratory, which can be used to study social interaction between humans and avatars.

An example of a possible thesis subject:

- Engaging human-robot interactions in healthcare for children and/or the elderly

Social robots are often deployed with 'special' user groups such as children and elderly people. Developing and evaluating robot behaviours for these user groups is a challenge as a proper understanding of their cognitive and social abilities is needed. Depending on the task, children for example need to be engaged and encouraged in a different way than adults do. What are effective robot behaviours and strategies to engage children and/or elderly people? How can these robot behaviours be evaluated in a proper way?

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Philips, Siemens, Honda, Mercedes, Google. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Robot Cognition could get:

- PhD Researcher on Cognitive-Affective Modelling for Social Robots

- PhD Researcher on Automatic analysis of human group behaviour in the presence of robots

- PhD Researcher on Automatic analysis of affective quality of conversations in human-robot interaction

- Advisor and innovation manager in the healthcare industry

- Social robotics and affective computing for robots expressing emotions

- Developer of control algorithms for using optic flow in drones

- Advisor for start-up company on developing new uses for tactile displays

- Team member in design of emotion recognition and training for autistic children

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.

See the website http://www.ru.nl/masters/ai/robot



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New for 2018, the LLM in LegalTech is an innovative and topical master’s programme, which explores how technologies such as Artificial Intelligence and Blockchain impact on legal services. . Read more

New for 2018, the LLM in LegalTech is an innovative and topical master’s programme, which explores how technologies such as Artificial Intelligence and Blockchain impact on legal services. 

Organisations from both the legal and the tech worlds will be involved in the delivery of the programme, which will offer opportunities to work with artificial intelligence systems; to develop LegalTech apps and solutions; to become comfortable working with Big Data, and to understand the legal and regulatory challenges associated with technology.

Artificial intelligence and related computing technologies are shaping the legal profession at an unprecedented rate. While lawyers must continue to defend the rule of law and to promote access to justice, they must also acquire the skills to embrace new technologies, innovate, and apply "LegalTech" in practice.

What is LegalTech?

Technology is transforming the nature of legal service delivery - from Artificial Intelligence and Blockchain, to online dispute resolution and digital platforms to improve Access to Justice.

Traditional areas of LegalTech such as case management, financial systems and legal research are being streamlined by innovative digital platforms and applications. These will make practices more efficient, more competitive and more relevant in a digital world, making sure that the Law is accessible to everyone.

 What are the benefits of the LLM in LegalTech?

You will acquire a range of skills and experiences that will complement your legal knowledge and equip you to drive innovation in legal practice. You will gain insights into how computational thinking can be related to legal processes and will understand how to deploy different technologies to aid legal practice.

What will I study?

You will take required and optional modules over two general topic areas - how AI is applied to the Law (e.g. introduction to theory, techniques, and tools) and how the Law is applied to AI (e.g. legal, regulatory and ethical impacts of automation and information access). You will learn AI concepts and work with AI tools to develop your own LegalTech solutions, gain experience working with “Big” and Small Data, and apply your knowledge in hands-on practical exercises.

Key Features of LLM in LegalTech

  • Be one of the UK’s first LLM in LegalTech graduates!
  • Gain the knowledge and experience to develop into a 21st century lawyer/legal service practitioner able to deploy different technologies to aid legal practice and to drive innovation across the profession.
  • Discover how Artificial Intelligence is applied to the Law (e.g. introduction to theory, techniques, and tools) and how the Law is applied to AI (e.g. legal, regulatory and ethical impacts of automation and information access).
  • Learn AI concepts and work with AI tools to develop your own LegalTech solutions, gain experience working with “Big” and Small Data, and apply your knowledge in hands-on practical exercises.

Topics in LLM in LegalTech

  • Artificial Intelligence and Law (Computer Science applied to Law)
  • Automating Legal Services
  • Computational thinking and programming for lawyers
  • Quantitative analysis and working with Big Data
  • Blockchain/distributed ledger technology
  • The Law and Artificial Intelligence (Law applied to Computer Science)
  • Rights and accountability in the Digital Economy
  • Legal services in a digital world
  • LegalTech entrepreneurship
  • Digital IP
  • Dissertation or project

Extra-curricular Activities

Throughout your studies, you will have the opportunity to take part in a number of extra-curricular activities to enhance their understanding of LegalTech. These include:

Careers and Employability

There are a broad range of traditional and specialist legal career opportunities available.

  • Lawyers
  • Legal engineers
  • Legal project managers
  • Legal data scientists
  • Legal risk managers
  • Legal technologists


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Investigating the true nature of intelligence is one of today’s most fascinating research avenues. Advances in the study of cognitive processes and models, natural language and perception, human knowledge, representation, and reasoning attest to this. Read more

Investigating the true nature of intelligence is one of today’s most fascinating research avenues. Advances in the study of cognitive processes and models, natural language and perception, human knowledge, representation, and reasoning attest to this. One of the scientific community’s key research objectives is the development of an intelligent robot. The Master of Artificial Intelligence explores and builds on this challenge, will you?

What's the Master of Artificial Intelligence about? 

The Master of Artificial Intelligence programme at KU Leuven explores and builds on these fascinating challenges. For many years, it has provided an internationally acclaimed advanced study programme in artificial intelligence. The multidisciplinary programme trains students from a variety of backgrounds - including engineering, sciences, economics, management, psychology, and linguistics - in all areas of knowledge-based technology, cognitive science, and their applications. The one-year programme, taught entirely in English, is the result of a collaboration between many internationally prominent research units from seven different faculties of the university. It allows you to focus on engineering and computer science, cognitive science, or speech and language technology.

Objectives

The AI program aims at instructing and training students on state of the art knowledge and techniques in Artificial Intelligence, with specific focus either on Engineering and Computer Science (ECS), on Speech and Language Technology (SLT) or on Big Data Analytics (BDA), depending on the selected option within the program. It aims at introducing the students to the concepts, methods and tools in the field.

It aims at instructing students on the achievements in a number of advanced application areas and make them familiar with their current research directions. It aims to bring students to a level of knowledge, understanding, skills and experience that are needed to actively conduct basic or applied research on an international level. In particular, it aims to provide students with a critical scientific attitude towards the central themes of A.I.

As a master-after-master program, it is assumed that the students entering this program have already achieved the general skills and attitudes defined for any master program. Nevertheless, it is also within the aims of the program to further strengthen the skills and attitudes, within the specific scientific context that AI offers.

ECS-option: In the ECS option, in addition to the above, the program aims at instilling a problem-solving attitude towards the practice of AI. Upon completion of the program, students should be familiar with the fundamentals of AI, be aware of its reasonable expectations, have practical experience in solving AI-problems and be acquainted with a number of advanced areas within the field.

SLT-option: In the SLT-option, in addition to the general aims, the program aims to provide all necessary background and skills which are required to fully understand and to actively participate in the fast developing multi-disciplinary field of Language and Speech. This includes a thorough understanding of the theories and models that shape the field, as well as practical experience with a variety of technologies that are used and currently developed.

BDA-option: In the BDA-option, in addition to the general aims, the program aims for the same additional goals as the ECS-option, but specialized to Big Data Analytics. In particular, it aims at instilling a problem-solving attitude towards the practice of Big Data Analytics. Upon completion of the program, students should be familiar with the fundamentals of Big Data Analytics, be aware of its reasonable expectations, have practical experience in solving BDA-problems and be acquainted with a number of advanced areas within the AI-subfield of BDA.

Career perspectives

With a Master's degree in artificial intelligence you will be welcomed by companies working in:

Information technology

  • Information technology
  • Data mining and Big Data
  • Speech and language technology
  • Intelligent systems
  • Diagnosis and quality control
  • Fraud detection
  • Biometric systems

You will also be qualified to work in banking or provide support for the process industry, biomedicine and bioinformatics, robotics and traffic systems. Some graduates go on to begin a PhD programme.



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Program Description. The Division of Global Affairs (DGA) offers a Master of Science (M.S.) degree in Global Affairs in residence. Read more

Program Description

The Division of Global Affairs (DGA) offers a Master of Science (M.S.) degree in Global Affairs in residence. It may be taken on a full-time or part-time basis. It is a multidisciplinary degree concerned with theoretically informed and problem-oriented approaches to transnational issues that interact with local issues. It is designed for practitioners in the Global Arena including business professionals, government employees, security professionals including the military, and those who are presently employed or plan careers with international governmental and non-governmental organizations. Forty (40) credits are required for the M.S. degree in Global Affairs. All students must complete:

  • Seven Areas of Inquiry (AIs) Courses with grades of B (3.0) or higher —21 credits​​​
  • One Research and Methodology Course —3 credits
  • Two Capstone Colloquia Series with grades of Pass (a colloquium is a lecture series of 5 to 6 presentations on a given topic organized by a core DGA faculty, which students must attend and write a 15 page paper on if they want to accumulate credit) —4 credits
  • One Foundation Course - (26:478:508; 26:790:508): Evolution of the Global System —3 credits
  • Three Elective Courses —9 credits; note: three electives may be joined with the applicable AI discipline to qualify for a certificate
  • Language Requirement— no credit; the language requirement is fulfilled by prior coursework, a major/minor, or demonstrated familiarity or fluency in another language. 

8 Areas of Inquiry

Ethics, Security, & Global Affairs

Global Governance

Human Security

Global Political Economy

International Law

History of International Business

Global Development

Human Rights & Mass Atrocities

Core courses

Areas of Inquiry Courses (AIs)

The Division of Global Affairs requires that students complete seven Areas of Inquiry (AI) courses. These courses are geared towards giving students the foundation they will need for future Global Affairs courses and endeavors in the global affairs field. Students must complete seven (7) of the eight courses with a grade of a B or higher, and are encouraged to take the courses early on in their studies. Students who do not receive a grade of B or higher in any AI course must retake the course. All AI requirements must be completed in residence. Transfer credits may not be used in fulfillment of AI requirements. The AI courses are listed below alongside their course number. 

  • Ethics, Security, and Global Affairs 
  • Global Governance 
  • Human Security 
  • Global Political Economy
  • International Law 
  • History of International Business
  • Global Development
  • Human Rights and Mass Atrocities

NOTE #1: M.S. students are strongly encouraged to take both a qualitative and a quantitative methodology course.

NOTE #2: Interested students can consider Internships or Independent Study as additional requirements.

NOTE #3: M.S. students must maintain a grade-point average of 3.0 or higher in all non-language courses taken at Rutgers University. If a student's academic performance falls below the expected standard, the DGA and the Graduate School-Newark may refuse the student the right of future registration and terminate studies. Students with an insufficient grade-point average may submit an appeal to the DGA Director. 

Time Limits

Students must complete their degrees within six years of admission into the M.S. program, regardless of whether students are part time or full time and regardless of whether they entered DGA with or without transfer credits. Students who fail to meet this deadline may be forced to withdraw from graduate studies at DGA.



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Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent… Read more

Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent - so that they are able to learn from experience, to derive implicit knowledge from the one given explicitly, to understand natural languages such as English, Arabic, or Urdu, to determine the content of images, to work collaboratively together, etc. The techniques used in AI are as diverse as the problems tackled: they range from classical logic to statistical approaches to simulate brains.

This pathway reflects the diversity of AI in that it freely combines a number of themes related to AI techniques, namely Making Sense of Complex Data, Learning from Data, Reasoning and Optimisation, and Advanced Web Technologies.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

Students following the Artificial Intelligence pathway have all the career choices and options as described for general Advanced Computer Science.

In addition, students of this pathway are ideally placed to work in positions requiring an understanding of modern AI formalism and technologies such as Natural Language Processing, Machine Learning, and Semantic Technologies. This includes the obvious positions in the games industry, but also positions in finance, commerce, and scientific research, and many more.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.



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A QUICKLY CHANGING AND CHALLENGING FIELD . Artificial Intelligence is a fast-paced and challenging field that is making visible inroads into our everyday life. Read more

A QUICKLY CHANGING AND CHALLENGING FIELD 

Artificial Intelligence is a fast-paced and challenging field that is making visible inroads into our everyday life. This Master's programme focuses on the theoretical symbolic foundations within Artificial intelligence. We examine the semantics of natural language and of reasoning and argumentation. Moreover, we also look at the foundations of autonomy and collaboration between distributed software systems. These are applied for instance in virtual characters in serious games, in logistic applications like train schedules and in autonomous cars. Other application areas are social simulation for policy management and change of behaviour.  

OUR OFFER 

The Master’s in Artificial Intelligence offers you an integrative and cutting-edge approach to the field from the viewpoints of Informatics, Logic, Cognition, Psychology, Philosophy, and Linguistics.

Students can choose from three tracks: 

Choosing from a broad range of courses you can tailor the programme to your personal interests within Artificial Intelligence.  

PROGRAMME OBJECTIVE 

As a graduate of the Artificial Intelligence programme, you will have a solid understanding of the logical, philosophical, and cognitive foundations of AI research. You will also have a good overview of the main AI techniques and an in-depth understanding of how to apply these techniques in at least one of the areas within multi-agent systems, reasoning, or cognitive processing. In addition, you will have the skills to carry out AI research in academic or R&D environments and to identify how AI techniques can provide intelligent solutions to IT problems in companies and organisations.



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What is intelligent behaviour? How can robots communicate with each other? In this programme you will learn how to design and implement intelligent systems. Read more
What is intelligent behaviour? How can robots communicate with each other? In this programme you will learn how to design and implement intelligent systems.

The core topics in The Master's programme Artificial Intelligence are: autonomous perceptive systems, cognitive robotics and multi-agent systems.

- Autonomous Systems
A robot taking samples and collecting information on the moon is an example of an autonomous system. It operates and carries out missions independently. Regardless of their surroundings, it responds with a certain intelligence. While traditional AI focuses on cognition and reasoning as isolated abilities, we strongly believe in perception as an active behavior, which is integrated into general cognition.

- Cognitive Robotics
The courses taught in the area of cognitive robotics are related to research in social robotics, to the origin of robotic communication and to the way in which robots recognize movement. Research is conducted at the Artificial Intelligence and Cognitive Engineeringinstitute.

- Multi-agent Systems
When a team of robots play footbal they have to communicate and cooperate with each other. This is an example of a multi-agent system. When designing these systems, techniques from computing science and logic are combined with knowledge about the interaction amongst humans and animals.

Why in Groningen?

- Be part of a Programme with excellent reviews
- Challenging graduation projects

Job perspectives

Once you have obtained your Master's degree in Artificial Intelligence, you can apply your skills in research & development, for instance air traffic and space labs, where you make sure that intelligent and innovative technologies are used during the design process. You could also choose to get a job at a research institute where you work as a researcher. This can be done at a university (PhD) or at a research institute like TNO. About 50% of our students chooses a career as a scientist.

Where do graduated master AI students work at the moment? Maarten van Grachten and Mathijs Homminga did the AI master in the old doctoral program and they specialized in very different directions. Mathijs works as a software engineer at the IT-company Evermind. He programs and implements innovative IT-projects for shops. Maarten is doing a PhD in Barcelona where he investigates how a computer can compose jazz music.

Job examples

- Industrial Research & Development
- PhD research position
- Software engineer

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Research profile. At the Centre for Intelligent Systems and their Applications (CISA) we enable computer systems to reproduce or complement human abilities, work with people, and support collaboration between humans. Read more

Research profile

At the Centre for Intelligent Systems and their Applications (CISA) we enable computer systems to reproduce or complement human abilities, work with people, and support collaboration between humans. We conduct world-leading research in the foundations of Artificial Intelligence (knowledge representation and reasoning, emergence of meaning, theory and ontology change, creativity, mathematical proof) and in intelligent collaborative systems (multiagent systems, social computation, scientific collaboration platforms, web semantics and linked data).

Our research methods are inspired by developing formal models of knowledge, reasoning, and interaction that can be used to understand and automate aspects of human intelligence, but are also understandable and usable to the human designers and users of AI systems.

To achieve this, we combine theoretical research into computational models, architectures, and algorithms with a strong element of applied research. This has led to a strong track record in using our methods to address real-world problems in healthcare, scientific collaboration, social computing, emergency systems, transportation, engineering, aerospace and others.

You'll find a wide range of research areas within CISA conducted in the four research groups the Institute currently hosts:

  • Agents and Multiagent Systems
  • Mathematical Reasoning
  • Planning & Activity Management
  • Data-Intensive Research

CISA includes one of the most innovative collaborations between research and business - our Artificial Intelligence Applications Institute (AIAI). Through its resources and the engagement of CISA staff and students in consultancy, training and joint projects, we help companies and government agencies to apply newly researched techniques.

Training and support

You will carry out research work within a research group under the guidance of a supervisor. You may also attend taught courses that are relevant to your research topic, as prescribed by your supervisor. You will be expected to attend seminars and meetings of relevant research groups. Periodic reviews of progress are conducted to assist with research planning.

A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.

The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.

Facilities

The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.

It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.

Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.

Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

While your research studies are a perfect route to a career in academia, your degree could also take you into the commercial world of applied AI and collaborative systems.

Software developers using AI technologies are among those who rely on the insights of our research. NASA and animation company Pixar are just two of the organisations that have recently employed our graduates.



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