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Robots have the potential to revolutionise society and the economy, working for us, beside us, and interacting with us. This EPSRC-sponsored programme will produce graduates with the technical skills and industry awareness to create an innovation pipeline from academic research to global markets. Read more

Research profile

Robots have the potential to revolutionise society and the economy, working for us, beside us, and interacting with us. This EPSRC-sponsored programme will produce graduates with the technical skills and industry awareness to create an innovation pipeline from academic research to global markets.

The robotics and autonomous systems area has been highlighted by the UK Government in 2013 as one of the eight Great Technologies that underpin the UK's Industrial Strategy for jobs and growth. Key application areas include manufacturing, assistive and medical robots, offshore energy, environmental monitoring, search and rescue, defence, and support for the ageing population.

The University of Edinburgh and Heriot-Watt University are jointly offering this innovative four-year PhD training programme, which combines a strong general grounding in current theory, methods and applications with flexibility for individualised study and a specialised PhD project.

Robotics and autonomous systems are increasingly studied beyond the range of classical engineering. Today robots represent one of the main areas of application of computer science and provide challenges for mathematics and natural science.

It is impossible to imagine transportation, warehousing, safety systems, space and marine exploration, prosthetics, and many other areas of industry, technology and science without robots. Robots are used in theoretical biology and the neurosciences as a model of behaviour.

Areas of interest specific to the center include: movement control, planning, decision making, bio- and neurorobotics, human-robot interaction, healthcare applications, robot soccer, neuroprosthetics, underwater robotics, bipedal walking, service robots, robotic co-workers, computer vision, speech processing, computer animation realistic simulations, and machine learning.

Training and support

Our four-year PhD programme combines Masters level coursework and project work with independent PhD-level research.

In the first year, you will undertake four or five masters level courses, spread throughout robotics, machine learning, computational neuroscience, computer architectures, statistics, optimization, sensorics, dynamics, mechanics, image processing, signal processing, modelling, animation, artificial intelligence, and related areas. You will also undertake a significant introductory research project. (Students with previous masters-level work in these areas may request to take less courses and a larger project.)

At the end of the first year, successful students will be awarded an MSc by Research by the University of Edinburgh. From this basis, the subsequent three years will be spent developing and pursuing a PhD research project, under the close supervision of your primary and secondary supervisors. The PhD will be awarded jointly by the University of Edinburgh and the Heriot-Watt University.

You will have opportunities for three to six month internships with leading companies in your area, and to participate in our industrial engagement programme, exchanging ideas and challenges with our sponsor companies.

Throughout your studies, you will participate in our regular programmes of seminars, short talks and brainstorming sessions, and benefit from our pastoral mentoring schemes.

Our user partners in industry include companies working in offshore energy, environmental monitoring, defence, assisted living, transport, advanced manufacturing and education. They will provide the real world context for research, as well as opportunities for reciprocal secondments, internships and involvement in our industrial engagement programme.

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

You will have access to the outstanding facilities in the Edinburgh Robotarium, a national facility for research into robot interaction, supporting the research of more than 50 world-leading investigators from 17 cross-disciplinary research groups.

Research groups at the Edinburgh Robotarium include humanoid movement control, underwater, land and airborne autonomous vehicles, human robot interaction, bio- and neuro-robotics, and planning and decision making in multirobot scenarios.

In addition, our research groups contain a diverse range of compute clusters for compute and data-intensive work, including a large cluster hosted by the Edinburgh Compute and Data Facility.

Career opportunities

Our aim is to produce innovation-ready graduates who are skilled in the principles of technical and commercial disruption and who understand how finance and organisation realise new products in start-up, SME and corporate situations.

We intend for our graduates to become leaders in the globally emerging market for autonomous and robotic systems that reduce risk, reduce cost, increase profit and protect the environment. This vision is shared by our industrial supporters, whose support for our internship programme indicates their strong desire to find highly qualified new employees.

Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.

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Data science is the study of the computational principles and systems for extracting knowledge from data, for maintaining data, and for ensuring its quality. Read more

Research profile

Data science is the study of the computational principles and systems for extracting knowledge from data, for maintaining data, and for ensuring its quality. Large data sets are now generated by almost every activity in science, society and commerce.

This EPSRC-sponsored programme tackles the question: how can we efficiently find patterns in these vast streams of data?

Many research areas in informatics are converging on the problem of data science. Those represented in the School include machine learning, databases, data management, optimization and cluster computing; and also the unstructured data issues generated in areas such as natural language processing and computer vision.

Our programme will allow you to specialise and perform advanced research in one of these areas, while gaining breadth and practical experience throughout data science.

A short sample of our research interests includes:

machine learning applied to problems in biology, astronomy, computer science, engineering, health care, and e-commerce
database theory and technology for managing unstructured data and for maintaining trust in data
big data and management of streaming data
management of unstructured data, including natural language processing, speech processing, and computer vision

You will be supervised by one of our 45 world-renowned faculty. You will also benefit from interacting with a group of 35 leading industrial partners, including Amazon, Apple, Google, IBM, and Microsoft.

This will ensure your research is informed by real world case studies and will provide a source of diverse internship opportunities. Moreover we believe that key research insights can be gained by working across the boundaries of conventional groupings.

Training and support

The MScR is the first part of a longer 1+3 (MSc by Research + PhD) programme offered by the School through the EPSRC.

Our four-year PhD programme combines masters level coursework and project work with independent PhD-level research.

In the first year, you will undertake six masters level courses, spread throughout machine learning, databases, statistics, optimization, natural language processing, and related areas. You will also undertake a significant introductory research project. (Students with previous masters-level work in these areas may request to take three courses and a larger project, instead of six courses.)

At the end of the first year, successful students will be awarded an MSc by Research. From this basis, the subsequent three years will be spent developing and pursuing a PhD research project, under the close supervision of your primary and secondary supervisors.

You will have opportunities for three to six month internships with leading companies in your area, and to participate in our industrial engagement programme, exchanging ideas and challenges with our sponsor companies.

Throughout your studies, you will participate in our regular programmes of seminars, short talks and brainstorming sessions, and benefit from our pastoral mentoring schemes.

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

Our research groups contain a diverse range of compute clusters for compute and data-intensive work, including a large cluster hosted by the Edinburgh Compute and Data Facility.

More broadly, 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 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

We intend for our graduates to become the research leaders, both in industry and academia, whose work will lead the way in data science. This vision is shared by our industrial supporters, whose support for our internship programme indicates their strong desire to find highly qualified new employees.

You will be part of a new generation of data scientists, with the technical skills and interdisciplinary awareness to become R&D leaders in this emerging area.

Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.

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Research in the Division of Genetics and Genomics aims to advance understanding of complex animal systems and the development of improved predictive models… Read more

Research profile

Research in the Division of Genetics and Genomics aims to advance understanding of complex animal systems and the development of improved predictive models through the application of numerical and computational approaches in the analysis, interpretation, modelling and prediction of complex animal systems from the level of the DNA and other molecules, through cellular and gene networks, tissues and organs to whole organisms and interacting populations of organisms.

The biology and traits of interest include: growth and development, body composition, feed efficiency, reproductive performance, responses to infectious disease and inherited diseases.

Research encompasses basic research in bioscience and mathematical biology and strategic research to address grand challenges, e.g. food security.

Research is focussed on, but not restricted to, target species of agricultural importance including cattle, pigs, poultry, sheep; farmed fish such as salmon; and companion animals. The availability of genome sequences and the associated genomics toolkits enable genetics research in these species.

Expertise includes genetics (molecular, quantitative), physiology (neuroendocrinology, immunology), ‘omics (genomics, functional genomics) with particular strengths in mathematical biology (quantitative genetics, epidemiology, bioinformatics, modelling).

The Division has 18 Group Leaders and 4 career track fellows who supervise over 30 postgraduate students.

Training and support

Studentships are of 3 or 4 years duration and students will be expected to complete a novel piece of research which will advance our understanding of the field. To help them in this goal, students will be assigned a principal and assistant supervisor, both of whom will be active scientists at the Institute. Student progress is monitored in accordance with School Postgraduate (PG) regulations by a PhD thesis committee (which includes an independent external assessor and chair). There is also dedicated secretarial support to assist these committees and the students with regard to University and Institute matters.

All student matters are overseen by the Schools PG studies committee. The Roslin Institute also has a local PG committee and will provide advice and support to students when requested. An active staff:student liaison committee and a social committee, which is headed by our postgraduate liaison officer, provide additional support.

Students are expected to attend a number of generic training courses offered by the Transkills Programme of the University and to participate in regular seminars and laboratory progress meetings. All students will also be expected to present their data at national and international meetings throughout their period of study.

Facilities

In 2011 The Roslin Institute moved to a new state-of-the-art building on the University of Edinburgh's veterinary campus at Easter Bush. Our facilities include: rodent, bird and livestock animal units and associated lab areas; comprehensive bioinformatic and genomic capability; a range of bioimaging facilities; extensive molecular biology and cell biology labs; café and auditorium where we regularly host workshops and invited speakers.

The University's genomics facility Edinburgh Genomics is closely associated with the Division of Genetics and Genomics and provides access to the latest genomics technologies, including next-generation sequencing, SNP genotyping and microarray platforms (genomics.ed.ac.uk).

In addition to the Edinburgh Compute and Data Facility’s high performance computing resources, The Roslin Institute has two compute farms, including one with 256 GB of RAM, which enable the analysis of complex ‘omics data sets.

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The Institute for Neuroscience has clinicians and scientists working together to understand the brain and behaviour. Read more
The Institute for Neuroscience has clinicians and scientists working together to understand the brain and behaviour. From the basic biology of neurons through to complex processes of perception and decision-making behaviour, we address how the mind, brain, and body work together and translate this knowledge into clinical applications for patient benefit.

We offer MPhil supervision in the following research areas:

Motor systems development, plasticity and function

We conduct clinical and preclinical studies of normal and abnormal development and plasticity of the motor system. We run functional studies and computer modelling of motor system activity throughout the neuraxis. We also research the development and assessment of novel therapies for motor disorders/lesions including stem cell and brain-machine interface.

Visual system development, plasticity and repair]]
We research the development and assessment of novel neuro-technological approaches to retinal dystrophy repair including brain-machine interface and stem cells. We use in vitro approaches to look at retinal development and visual system wiring.

[[Neural computation and network systems
We conduct experimental and theoretical (computational) studies aimed at understanding how neurones throughout the brain interact in localised networks to compute complex tasks. Our research looks at the role of network activity in a wide range of neurological, neurodegenerative and psychiatric disorders.

Auditory neuroscience

We conduct clinical and preclinical studies aimed at understanding the brain mechanisms involved in detection, discrimination and perception of sound. We are interested in how these mechanisms are affected in individuals with brain disorders, including dementia, autism and stroke.

Pain

Our research focuses on:
-Understanding mechanisms underlying pain, analgesia, and anaesthesia
-The development of methods to assess pain and to alleviate pain in animals and humans

Psychobiology

We conduct studies in laboratory animals, healthy volunteers and patient populations investigating the mechanisms underlying mood, anxiety and addiction disorders and their treatment. Allied research looks at normal neuropsychology, and the physiology and pharmacology of neurotransmitter and endocrine systems implicated in psychiatric disorders.

Neurotoxicology

Our research focuses on delineating the effects and understanding the mechanisms of action of established and putative neurotoxins, including environmental and endogenous chemicals, and naturally occurring toxins.

Forensic psychiatry and clinical psychology

Our research covers:
-The assessment, treatment and management of sex offender risk
-Development and assessment of cognitive models
-Cognitive behavioural therapy (CBT) treatment for bipolar disorder, psychosis, anxiety and developmental disorders
-Developmental disorders of perception and cognition

Systems and computational neuroscience

We conduct theoretical (computational) and experimental studies aimed at understanding the neuroanatomy, neuropharmacology of vision, visual attention and episodic memory.

Behaviour and evolution

Many research groups take an evolutionary and comparative approach to the study of brain and/or behaviour, comparing brain function and behaviour among such disparate groups as insects, birds and mammals, and studying the ecological and evolutionary functions of behaviour. Much of our work is at the forefront of the fields of neuroethology, behavioural ecology and comparative cognition, and has important implications for the study and practice of animal welfare.

Visual perception and human cognition

We research:
-Colour and depth perception - perception of natural scenes
-Psychophysics and attention - memory
-Word learning in children
-Body image dysfunction
-Visual social cognition and face processing
-Advertising and consumer behaviour

Pharmacy

Our new School of Pharmacy has scientists and clinicians working together on all aspects of pharmaceutical sciences and clinical pharmacy.

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Take advantage of one of our 100 Master’s Scholarships to study Logic and Computation at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Logic and Computation at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Logic is the basis for reasoning about what we can express and compute, having a profound influence in philosophy, linguistics, mathematics, computer science, and electronics. Since the invention of computers, logic has always been the primary source of ideas and techniques for the theoretical and practical development of programming.

Today, as the scope of programming technologies expands, and the horizon of applications widens, research in logic and its applications in software and hardware development is booming. In industry, formal methods are an integral part of system development, e.g., in automotive electronics, avionics, and chip design.

The MRes Logic and Computation course will teach you about advanced techniques in logic and their applications in research problems in computer science. You will receive an elite education of direct relevance to research and development problems in contemporary information and communication technology (ICT).

Key Features

Teaching score of Excellent.

Highest percentage of top-class researchers of any Computer Science department in Wales – and only 12 in the UK have higher.

70% of the research activity assessed as world-leading or internationally excellent.

Our industrial programme IT Wales which can arrange vacation employment placements.

A state-of-the-art education.

Friendly staff, committed to the highest standards.

A university with high success rate, low drop-out rate, and excellent student support.

Swansea's Library spends more per student on books and other resources than any other university in Wales, and most in the UK.

Course Content

Research Component

The main part of the MRes in Logic and Computation is a substantial and challenging project involving cutting edge research. The completion of such a project will give you the ability and confidence to pursue a successful career in industrial research and development, or to proceed to academic PhD studies.

Taught Component

In seminars and reading courses you will enter the world of research by studying general topics in theoretical computer science as well as special topics for your research project. Guided by your supervisor you will conquer new technical subjects and learn to critically assess current research.
Lecturers and students will meet regularly to discuss recent developments and give informal talks. Topics of the seminars are chosen in accordance with the research projects, and will cover material such as:

Theorem proving techniques
Formal program verification
Algebraic and coalgebraic specification
Modelling of distributed systems
Advanced methods in complexity theory
Additionally you will choose selected taught modules covering important topics such as Critical Systems, IT Security, Concepts of Programming
Languages, Artificial Intelligence Applications, Design Patterns and Generic Programming.

Facilities

The Department is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

90% of Swansea’s Computer Science graduates are in full-time employment or further study within six months of graduating (HESA June 2011).

Some example job titles from the HESA survey 2011:

Software Engineer: Motorola Solutions

Change Coordinator: Logica

Software Developer/Engineer: NS Technology

Workflow Developer: Irwin Mitchell

IT Developer: Crimsan Consultants

Consultant: Crimsan Consultants

Programmer: Evil Twin Artworks

Web Developer & Web Support: VSI Thinking

Software Developer: Wireless Innovations

Associate Business Application Analyst: CDC Software

Software Developer: OpenBet Technologies

Technical Support Consultant: Alterian

Programming: Rock It

Software Developer: BMJ Group

Research

The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).

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The Department of Zoology at UBC is internationally renowned for its research in a variety of modern biological sciences, including ecology, evolution, physiology, neurobiology, cell biology and development. Read more
The Department of Zoology at UBC is internationally renowned for its research in a variety of modern biological sciences, including ecology, evolution, physiology, neurobiology, cell biology and development. The department has many strong interdisciplinary connections between different areas of research.

Zoology has a solid computing infrastructure of computer labs, compute servers, loaner equipment, colour and poster printers, and three computing support staff for knowledgable help.

Program Overview

Zoology encompasses over 50 principal investigators. Research interests of faculty members can be divided into several broad categories with substantial overlap of interest and collaboration among these arbitrary groups. The program vigorously promotes integrative research in biology and actively participates in several interdisciplinary programs, including the graduate programs in genetics, neuroscience, applied mathematics, and resource management.

Zoology offers a wide variety of research programs leading to the Master of Science and Doctor of Philosophy in the following areas: cell and developmental biology, community and population ecology, comparative physiology and biochemistry, neurobiology, and evolutionary biology.

In addition Zoology is actively involved in several interdisciplinary programs of instruction and research including:
- Fisheries Centre
- Centre for Biodiversity Research
- Centre for Applied Conservation Research (CACR), Faculty of Forestry
- Genetics Program
- ICORD (International Collaboration on Repair Discoveries)
- Institute of Applied Mathematics
- BC Cancer Research Centre
- Life Sciences Institute

Quick Facts

- Degree: Master of Science
- Specialization: Zoology
- Subject: Life Sciences
- Mode of delivery: On campus
- Program components: Coursework + Thesis required
- Faculty: Faculty of Science

Research focus

- Cell and Developmental Biology: molecular and genetic bases of development and cellular function
- Comparative Physiology: aspects of animal physiology from a comparative perspective, particularly those mechanisms underlying adaptive responses to environmental constraints
- Ecology: blends field ecology and natural history with ecological theory and conservation biology
- Evolution: encompasses evolutionary ecology, evolutionary genetics, conservation genetics, theory, and systematics

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Why does one car have more air resistance than another? How can a satellite be kept in an orbit around the earth? Applied mathematicians provide the necessary theoretical background to such questions. Read more
Why does one car have more air resistance than another? How can a satellite be kept in an orbit around the earth? Applied mathematicians provide the necessary theoretical background to such questions.

Applied Mathematics is concerned with the development and exploitation of mathematical tools for the analysis and control of technological problems. Mathematical modelling of the problem at hand plays a basic role, followed by (numerical) analysis and (computer) simulation. Interaction with other disciplines and with specialists in the fields of application is essential.

Two specialisations

- Systems and control
This specialisation deals with the mathematics behind designing stable controllers for satellites, purification plants or more general technical processes. Questions that arise include: is it possible to suppress perturbations in a system? Or, how can one stabilize and control a system without causing shocks?

- Computational science and numerical mathematics
This specialisation emphasizes modelling, analysis and the simulation of fluid flow problems. Although the applications can be quite diverse, the basic mathematical methods are much the same. If you are capable of computing the flow of air, you are able to predict the weather, and to design cars and aeroplanes. People who can simulate the flow of water can compute the optimal shape of ships, harbours and dikes.

Why in Groningen?

- Typical for Applied Mathematic in Groningen: the connection between mathematical theory and real-life problems
- You can combine courses from both Mathematics and Applied Mathematics
- Courses include related fields, e.g. Econometrics and Physics
- Internship and research opportunities

Job perspectives

A Master's degree in Applied Mathematics opens up many job opportunities. During the Master's programme you will learn to think in a logical, systematic, and problem-oriented way in a multidisciplinary environment. After having finished the programme you will be able to apply mathematics to a technical problem, and hence to work at the interface between theory and practice. These qualities are highly appreciated by employers.

Job opportunities are available in industrial companies, research institutes, as well as in universities. Examples of companies looking for applied mathematicians include Gasunie, Philips, Stork, Shell, Corus, KPN and small engineering bureaus. Examples of research institutes are the National Aerospace Laboratory (NLR, the picture on these pages comes from the NLR), WL/Delft Hydraulics, KNMI and TNO.You can start a university career by working as a PhD student, which means working for four years on a research project and writing a thesis. After having successfully defended this thesis, you will be awarded a PhD degree. Afterwards you can continue an academic career or start a career in industry.

Job examples

- Research institutes
- Engineering bureaus
- Industrial companies
- Universities

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Come to our Postgraduate Open Day on Friday 10 February to find out more!. By studying this Masters course you’ll be well placed to join one of the most performance-driven applications of computer science – the multi-billion pound global games industry. Read more
Come to our Postgraduate Open Day on Friday 10 February to find out more!

By studying this Masters course you’ll be well placed to join one of the most performance-driven applications of computer science – the multi-billion pound global games industry.

As a graduate of this course you will work at the top-end of the games industry and will develop computer graphics on high-performance platforms, or write engines for the next generation of games.

This course will build on your computer science knowledge to specialise in computer graphics, where games programmers must push computing resources to the limit, using deep understanding of architecture and high-performance programming to generate new levels of graphical realism and visual effects on cutting-edge hardware platforms

You can be sure that what you learn will be the technical skills required by industry as this course has been developed in collaboration with a prestigious steering group from industry comprising:

- Barog Game Labs
- Double Eleven
- Epic Games
- NVIDIA
- Team 17
- Sumo Digital
- Weaseltron

During this course you will develop a proficiency in low-level programming (C++, Graphic and Compute shaders), a thorough understanding of multi-core and many-core programming techniques, game engine and tool development techniques, and fundamental insight into graphics and the practical techniques used in games, including geometric models, animation and simulation, and advanced methods for visual realism.

Keywords: games development, gaming, games engineering, graphics, computing, computer science

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The International Master's program in Data Analytics enables students to take up challenging research in the interdisciplinary field with major focus on data analytics. Read more

Course description

The International Master's program in Data Analytics enables students to take up challenging research in the interdisciplinary field with major focus on data analytics.
During the program you will learn deeply about bleeding edge models and methods in machine learning as well as about turning ideas into code and thus design, implement and run your own experiments. Training on a largescale compute cluster and big data applications is part of the program, too.
During your study project you will learn how to write research proposals, how to manage research projects as a team and how to present results to a critical.

The Data Analytics program combines complex mathematical and statistical models and methods from machine learning with problems from an application domain using tools and techniques for processing Big Data. The programs is structured in a way that it builds on the core data modeling and data analytics knowledge with application on the large volume of real-world data using modern big data technologies such as the Apache Hadoop, Apache Spark, NoSQL etc.

Core Modules

* Machine Learning
* Advanced Machine Learning
* Modern Optimization Techniques
* Programming machine Learning
* Big Data Analytics
* Distributed Data Analytics
* Planning and Optimal Control

Application and Admission

The program starts at University of Hildesheim in the beginning of October every year. For details on how to apply please visit our website http://www.ismll.uni-hildesheim.de/da

FAQs

The list of frequently asked questions can be found here http://www.ismll.uni-hildesheim.de/da/faq_en.html. We recommend you to go through these questions. If you didn't find your answer, please feel free to contact us.

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Choosing to take a Master of Science in Mathematics and Statistics at Acadia will deepen your mathematical knowledge, and develop your research and analytical skills. Read more
Choosing to take a Master of Science in Mathematics and Statistics at Acadia will deepen your mathematical knowledge, and develop your research and analytical skills. At the same time, you can earn your degree while gaining experience working and researching in industry.

Acadia's graduate program in mathematics and statistics offers you an exciting opportunity to earn your degree and tackle a significant research problem while also participating in our award-winning co-operative education option and gaining industry work experience. You will take courses that will broaden your knowledge and also prepare you to work on your chosen research project. Our co-operative education option allows you to gain eight months of industry experience work terms or internships. A special feature of the program is to be able to align your work experience and research project, allowing you to more deeply understand the importance and relevance of the research problem.

Be Inspired

In our program, you will benefit from the small school advantage – close contact with your supervisor and a program best-suited to your interests – while also being able to participate in a wide range of research that Acadia faculty conduct. In our department, you can pursue research into tidal energy in the Bay of Fundy, fractal images, games on graphs, statistical learning, big data, computer experiments, cryptography, number theory, scheduling theory, and statistical applications in agriculture, biology, and medicine.

Our department is associated with the Acadia Centre for Mathematical Modeling and Computation, ACENet and Compute Canada, which provide expertise and resources for applying computational resources towards solving problems in the mathematical sciences. The Statistical Consulting Centre creates opportunities to support local projects, and to consult on other research projects at the institution. Acadia's faculty engage in projects with local businesses, federal and provincial government agencies, the local tidal power and agricultural industries, and a variety of businesses nationally and internationally.

Research Interests

-Hugh Chipman: Tree models, variable selection, Bayesian methodology, data mining
-Nancy Clarke: Graph theory, combinatorics, design theory and game theory
-Eva Curry: Digital representations for vectors and connections to wavelet theory, iterated function systems, probability, and number theory
-Jeff Hooper: Algebraic number theory, cryptography
-Richard Karsten: Models of ocean circulation, climate modelling
-Wilson Lu: Survey sampling, replication methods, survey confidentiality, computer experiment design
-Franklin Mendivil: Image processing, stochastic optimization, fractal analysis
-Jianan Peng: Order restricted inference, multiple comparisons, nonparametric statistics
-Pritam Ranjan: Computer experiments, sequential designs, combinatorial designs
-Paul Stephenson: Machine scheduling, optimization algorithms
-Holger Teismann: PDE, control theory, non-linear optics
-Ying Zhang: Statistical computing, time series analysis, applied statistical modelling

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