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Masters Degrees (Cyber-Physical Systems)

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The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. Read more
The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. The curriculum is very flexible. Students can compile their individual study plans based on their background and interests. It is also a very practical program. In addition to lectures and tutorials, students will complete two seminars, one or two projects and the master thesis.

In the beginning students will choose one or two key courses. Key courses are courses which introduce the students to the research areas represented at the Department of Computer Science. The following key courses are offered:

• Algorithm Theory
• Pattern Recognition
• Databases and Information Systems
• Software Engineering
• Artificial Intelligence
• Computer Architecture

After that, students can specialize in one of the following three areas:

• Cyber-Physical Systems
• Information Systems
• Cognitive Technical Systems

Here are some examples of subjects offered in the three specialization areas:

Cyber-Physical Systems:

• Cyber-Physical Systems – Discrete Models
• Cyber-Physical Systems – Hybrid Control
• Real Time Operation Systems and Reliability
• Verification of Embedded Systems
• Test and Reliability
• Decision Procedures
• Software Design, Modeling and Analysis in UML
• Formal Methods for Java
• Concurrency: Theory and Practice
• Compiler Construction
• Distributed Systems
• Constraint Satisfaction Problems
• Modal Logic
• Peer-to-Peer Networks
• Program Analysis
• Model Driven Engineering

Information Systems:

• Information Retrieval Data Models and Query Languages
• Peer-to-Peer Networks
• Distributed Storage
• Software Design, Modeling and Analysis in UML
• Security in Large-Scale Distributed Enterprises
• Machine Learning
• Efficient Route Planning
• Bioinformatics I
• Bioinformatics II
• Game Theory
• Knowledge Representation
• Distributed Systems

Cognitive Technical Systems:

• Computer Vision I
• Computer Vision II
• Statistical Pattern Recognition
• Mobile Robotics II
• Simulation in Computer Graphics
• Advanced Computer Graphics
• AI Planning
• Game Theory
• Knowledge Representation
• Constraint Satisfaction Problems
• Modal Logic
• Reinforcement Learning
• Machine Learning
• Mobile Robotics I

We believe that it is important for computer science students to get a basic knowledge in a field in which they might work after graduation. Therefore, our students have the opportunity to complete several courses and/or a project in one of the following application areas:

• Bioinformatics
• Educational Sciences
• Geosciences
• Cognitive Sciences
• Mathematics
• Medicine
• Meteorology
• Microsystems Engineering
• Physics
• Political Sciences
• Psychology
• Sociology
• Economics

In the last semester, students work on their master’s thesis. They are expected to tackle an actual research question in close cooperation with a professor and his/her staff.

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Power ahead and make your postgraduate studies really count in the Department of Electronic and Computer Engineering. The recent evolution of Electronic and Computer Engineering has been developed into a wide-ranging discipline covering technologies critical to the growth of the knowledge economy. Read more
Power ahead and make your postgraduate studies really count in the Department of Electronic and Computer Engineering. The recent evolution of Electronic and Computer Engineering has been developed into a wide-ranging discipline covering technologies critical to the growth of the knowledge economy.

Networking, wireless communications, multimedia signal processing, microelectronics, microprocessors, IC design, opto-electronics, display technologies, and control and robotics all fall into this exciting discipline. Advanced training in these fields opens up a wealth of career opportunities in the manufacturing industry, business sector, government and universities worldwide.

The Department has gathered a talented faculty team, with PhDs from the world's top universities, and is equipped with state-of-the-art facilities to enable pioneering research and multimedia teaching to be carried out. We have over 40 teaching faculty members, over 300 research postgraduate students and are committed to world-class research and excellence in teaching, leading to significant results with international impact.

The Department's goal is to prepare students to become leading academics, top quality engineers or productive managers in the ever-changing high-technology world.

The MPhil program is designed for those interested in pursuing a career in research and development in industry or academia, and is an excellent preparation for a PhD degree. Students are required to undertake coursework and successfully research and defend a thesis.

Research Foci

The Department's research concentrates on six pillar areas:
Solid-State Electronics and Photonics
Topics related to Microelectronics, Nanoelectronics, Large Area Electronics, Power and Energy-Efficient Electronic Devices, High-Speed Electronics, Semiconductor Materials, Devices and Fabrication Technology, Micro-Electro-Mechanical Systems (MEMS), Displays, Optoelectronics, Organic Light-Emitting Diodes (OLEDs), Solid-State Lighting, Liquid-Crystal Displays, Liquid-Crystal Photonics, Silicon Photonics, Optical Communications and Interconnects, Solar Cells, Epitaxy of Compound Semiconductors by MOCVD.

Integrated Circuits and Systems
Topics related to Digital, Analog and Mixed-Signal Integrated Circuits (IC) Design, VLSI Design, Embedded Systems, Network-on-Chip and Multiprocessor System-on-Chip, Circuit and System Simulation and Verification Tools. Advanced topics include RF and mm-Wave IC and Systems, Data Converters, Power Management IC, High-Speed Optical Communication Transceiver, Image and Bio-Medical Sensors, Signal Processing and System Architectures, Design Automation, Computer Architecture, Reconfigurable System and Hardware/Software Codesign.

Wireless Communications and Networking
Topics related to Physical Layer, Signal Processing, Coding and Information Theory, Networking as well as New Architecture for Next Generation 5G Wireless Communications, Massive MIMO and Cloud Radio Access Networks, Interference Management, Heterogeneous Networks, Green Communications, Tactile Wireless Systems For Machine Type (MTC), Device-To-Device (D2D) and Multimedia Communications, Integration of Control and Wireless Communication Theory, Display-Smart Mobile Communications And Interactions, Network Coding Theory and Applications, Cross-Layer Stochastic Optimization, Distributed Algorithms and Optimisations, Big Data Systems, Social Media and Cyber-Physical and Social Computing Systems, Self-Organising Networks, Cloud Computing and Virtualisation.

Biomedical Engineering
Topics related to Medical Imaging, Biomedical Optics and Biophotonics, Neuroengineering, Medical Electronics, Bioinformatics/Computational Biology and Biomedical Microdevices and BioMEMS.

Control and Robotic Systems
Topics related to Control and Optimization (including System Theory, Optimization Theory, Detection and Estimation, Financial Systems, Networked Sensing and Control), Robotics and Automation (including UAV, Next-Generation Industry Robots, Medical/Healthcare Robotics, and Autonomous Systems).

Signal, Information and Multimedia Processing
Topics related to Digital Signal Processing of Video, 3D, Image, Graphics, Audio, Speech, Language, Biomedical Data, Financial Data, and Network Data. Specific topics include Signal Capture, Conditioning, Compression, Transformation, Playback and Visualization, Data Analysis, Information Theory, Error Correction, Cryptography, Computer Vision, Pattern Recognition, Machine Learning, Language Understanding, Translation, Summarization, Retrieval, Multi-Lingual and Multi-Modal Processing, and Embedded Systems.

Facilities

There are extensive facilities available to support the Department's programs. Laboratories for research and teaching encompass: advanced VLSI design and testing analog, automatic-control, biomedical instrumentation, broadband networks, computer networks and system integration, digital electronics and microprocessors, electro-optics, fine-line lithography, integrated power electronics, machine intelligence, optical device characterization, robot manipulation, signal processing and communication and wireless communication.

Relevant central facilities, research centers and research institutes include: the Automation Technology Center, Center for Networking, Center for Wireless Information Technology, Multimedia Technology Research Center, Nanoelectronics Fabrication Facility, Photonics Technology Center, Semiconductor Product Analysis and Design Enhancement Center.

In addition to the University's central computing facilities, the Department has over 200 Linux/Solaris workstations and over 900 PCs and Apple computers. Both industrial standard and research-oriented software are used by faculty and students for teaching and research.

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The MSc in Cyber Security and Management is designed for those wishing to develop a career as a cyber security professional, or to take a leading technical or managerial role in an organisation critically dependent upon data and information communication technology. Read more

Designed for

The MSc in Cyber Security and Management is designed for those wishing to develop a career as a cyber security professional, or to take a leading technical or managerial role in an organisation critically dependent upon data and information communication technology.

It is suitable for those from a computer science or information technology education background. The programme is also able to cater for those with no formal studies in computer science but where significant interest in cyber security can instead be demonstrated.

The Course Provides:

1. Cyber Security in the UK has become a ‘tier 1’ priority alongside international terrorism and major national incidents. The serious threats emerging from the cyber-sphere are a recognised phenomenon worldwide and as such studies in cyber security are strategically important on a global scale.

2. Our goal for the MSc programme is to give focus to the strategic deployment and implementation of Cyber Security within an organization. We want to develop strategic thinkers who understand the Cyber threat to an organization and its resources and are able to build and support secure systems that support the strategic growth of a business.

3. The course covers all aspects of Cyber Security including network security, computer security and information security. You will learn the most important technical concepts of security—such as encryption, intrusion detection, penetration testing, access control, digital forensics and investigation, risk management, security governance and network security.

4. Alongside this, the course focuses on the business context so that students can progress their careers more rapidly through organisations and aim very particularly at management positions.

When you study the MSc Cyber Security and Management at Warwick, you will gain an unparalleded exposure to industry. All taught modules contain considerable input from industry experts who, through case studies and guest lectures, contribute to the design and delivery of material making for a vey rich learning environment.

An example of some of the companies involved in the CSM programme since it was launched in 2012 include HP, Amethyst Consulting, Deep Secure Ltd, Siskin Technology, SOCA (Serious Organised Crime Agency), CSC, VMware, OCSIA, Nottingham Police, Mozilla, Metropolitan Police, Kaspersky, Berwin Leighton Paisner, Telefonica, IBM, Blackstage Forensics, Derbyshire NHS Trust and Nettitude.

You will have additional opportunity to engage with industry through industry visits, conferences, and mentoring or advice from industry experts at key stages of your work.

Course Content

Students study nine taught modules as part of the programme of study.
Core Modules:
1. Security Architectures and Network Defence
2. Cryptosystems and Data Protection
3. Information Risk Management and Governance
4. Industrial Espionage and Counterfeiting
5. Digital Forensics

Elective Modules (3 from this list):
1. Cyber Intelligence and Operations
2. Cyber-Physical Systems
3. Enterprise Cyber Security
4. Globalisation and Outsourcing
5. Financial Analysis and Control Systems
6. Organisations, People and Performance
7. Leadership

A ninth module to be selected from the full list of WMG elective modules.

Learning Style

The taught component of the course is highly interactive and varied with a mixture of lectures, syndicate or group work, practical and lab based work, and technology enabled learning.
Class sizes are kept to a maximum of 30 students per class.
Module leaders are experts in their fields and are supported by external speakers working in organisations at the forefront of their fields.
Assessment is through Post Module Assignment based on the learning objectives of each respective module.
50% of the Masters credit is achieved through your individual project or dissertation, for which you will have close 1-1 supervision
Each module will usually be delivered in intensive one-week blocks so you are fully immersed in the subject area for that period. These one-week sessions are scheduled at intervals from October through to June.

After Your Graduate

Graduates can expect to go on to work within corporate information - security and technology teams, consultancies, government information-security departments, management tracks in information critical organisations and cyber security related research.

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Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies. Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. Read more
Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies.

Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. As well as anyone who holds an undergraduate degree in technology-based disciplines such as Computer Science, Software Engineering, Web Technologies, Computer Engineering, Mathematics and Electronics.

This masters is unique as it provides you with a fundamental understanding of the architectures of Big Data systems as well as developing the enhanced skills in software application development and data analytics solutions that you need.

It is our aim to increase skills in the new technology areas that business and industry are rapidly adopting. These include big data architectures, cloud computing, web technologies, data analytics (especially SAS and IBM Watson Analytics), big data computing platforms and the ever-expanding sources of data related to the Internet of Things.

This course has several different available starts and study formats - please view the relevant web-page for more information:
SEPTEMBER 2017 (Part Time) - http://www.gcu.ac.uk/ebe/study/courses/details/index.php/P02870-1PTA-1718/Big_Data_Technologies_(Part-time)?utm_source=ZZZZ&utm_medium=web&utm_campaign=courselisting

JANUARY 2018 (Full Time) - http://www.gcu.ac.uk/ebe/study/courses/details/index.php/P02860-1FTAB-1718/Big_Data_Technologies?utm_source=ZZZZ&utm_medium=web&utm_campaign=courselisting

JANUARY 2018 (Part Time) - http://www.gcu.ac.uk/ebe/study/courses/details/index.php/P02870-1PTAB-1718/Big_Data_Technologies_(Part-time)?utm_source=ZZZZ&utm_medium=web&utm_campaign=courselisting

Programme Description

The MSc in Big Data Technologies equips students with the fundamental knowledge and practical skills required to enter the exciting and challenging world of Big Data.

The programme takes a technology-focused approach to help students gain valuable skills that can be applied immediately within business and industry. Students will also build expertise in the key enabling technologies of cloud computing and will gain skills in one of the most exciting current areas of Big Data computing, the Internet of Things.

Why Study this Programme

This programme will equip students with the fundamental knowledge and skills of the core technologies for harnessing the big data challenges, including capture, curation, storage, integration, sharing, search, analysis, mining of large distributed unstructured datasets.

Studies on this programme are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cyber security, Internet of Things and cyber-physical systems. Of parallel importance in our programme is to cultivate the professionalism which is expected within the industry.

With all the future-proofing capabilities synthesised coherently together, graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse big data application domains.

What you'll learn

Students complete six taught modules.

Trimester A:
-Cloud Computing and Web Services
-Big Data Landscape
-Data Analytics.

Trimester B:
-Big Data Platforms
-Internet of Things
-IT Professional Issues and Project Methods.

Trimester C:
-MSc Dissertation

Work Placement

Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.

Assessment

Assessment is used to demonstrate achievement of learning outcomes. The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.

Career Opportunities

Graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse Big Data application domains.

This programme provides key skills for those seeking employment or career enhancement as Big Data systems developers, architects and administrators, and Big Data technologist for businesses and organisations in diverse domains from engineering industries, environmental surveillance, smart cities, to service type industries.

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The MSc in Cyber Security Engineering is designed for those wishing to develop a career as a cyber security professional. Cyberspace comprises the network of digital devices, used to store, modify and communicate information. Read more

Designed for

The MSc in Cyber Security Engineering is designed for those wishing to develop a career as a cyber security professional.

Cyber Security

Cyberspace comprises the network of digital devices, used to store, modify and communicate information. It is global, interactive and completely changes our environment. It extends beyond the Internet, mediating interaction between individuals and groups.
Our world is increasingly shaped by cyberspace. Opportunities for interaction are emerging in ways, only imagined by previous generations. As the influence of cyberspace in our lives continues to grow, so does the associated security risk.
As organisations worldwide harness the opportunities of cyberspace, they create huge demand for cyber security professionals. Cyber security professionals who can function at various strata within an organisation - server room, operations room, board room - you choose. Their task is beguilingly simple: enable the good and prevent the bad.

GCHQ Certification

GCHQ, the UK government's National Technical Authority for Information Assurance, identified the shortage of cyber professionals as a concern that needed to be addressed. Part of their strategy was to identify cyber security master's courses that would "... help prospective students make better informed decisions when looking for a highly valued cyber security qualification".

Course Content

You will study a broad range of cyber security topics. Some focus on technology, some on people, some on organisations. Insofar as possible, we seek to avoid teaching topics in silos of narrow expertise. Throughout, the practical application of insight is valued equally with abstract analytical skill. The following should give you a sense of the course content:
◾Cryptography
◾Counterfeiting
◾Risk
◾Digital forensics
◾Governance
◾Data protection
◾Network security
◾Intelligence
◾The enterprise cyber perspective
◾Security architecture
◾Industrial espionage
◾Cyber-physical systems
◾Standards and guidance
◾Cyber security research

Teaching Style

Tutors adopt their own distinctive style within their taught weeks. Most modules are taught by more than one tutor, which, together with the wide range of guest speakers, gives real breadth of insight into any topic. The external input is especially evident in the Enterprise Cyber Security module where colleagues from IBM make a substantial contribution to the week's activities.

After You Graduate

Graduates can expect rapid career progression in within a wide range of organisations relating to cyber security in a range of roles.

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Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies. Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. Read more
Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies.

Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. As well as, anyone who holds an undergraduate degree in technology-based disciplines such as Computer Science, Software Engineering, Web Technologies, Computer Engineering, Mathematics and Electronics.

Unlike many data science MSc courses, this masters provides you with a fundamental understanding of the architectures of Big Data systems as well as the enhanced skills in software application development and data analytics solutions that you need.

It is our aim to increase skills in the new technology areas that business and industry are rapidly adopting. These include big data architectures, cloud computing, web technologies, data analytics (especially SAS and IBM Watson Analytics), big data computing platforms and the ever-expanding sources of data related to the Internet of Things.

Programme Description

The MSc in Big Data Technologies equips students with the fundamental knowledge and practical skills required to enter the exciting and challenging world of Big Data.

The programme takes a technology-focused approach to help students gain valuable skills that can be applied immediately within business and industry. Students will also build expertise in the key enabling technologies of cloud computing and will gain skills in one of the most exciting current areas of Big Data computing, the Internet of Things.

Work Placement

Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.

Assessment

Assessment is used to demonstrate achievement of learning outcomes. The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.

Career Opportunities

Graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse Big Data application domains.

This programme provides key skills for those seeking employment or career enhancement as Big Data systems developers, architects and administrators, and Big Data technologist for businesses and organisations in diverse domains from engineering industries, environmental surveillance, smart cities, to service type industries.

Why Study this Programme

This programme will equip students with the fundamental knowledge and skills of the core technologies for harnessing the big data challenges, including capture, curation, storage, integration, sharing, search, analysis, mining of large distributed unstructured datasets.

Studies on this programme are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cyber security, Internet of Things and cyber-physical systems.

Of parallel importance in our programme is to cultivate the professionalism which is expected within the industry.

With all the future-proofing capabilities synthesised coherently together, graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse big data application domains.

What you'll learn

Students complete six taught modules.

Trimester A:
-Cloud Computing and Web Services
-Big Data Landscape
-Data Analytics

Trimester B:
-Big Data Platforms
-Internet of Things
-IT Professional Issues and Project Methods

Trimester C:
-MSc Dissertation

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The future of information and communication technology (ICT) is driven by mobile and networked embedded systems. Read more

About Mobile and Embedded Systems

The future of information and communication technology (ICT) is driven by mobile and networked embedded systems: tomorrow’s digital cities, Industry 4.0, cyber-physical systems (CPS) and the Internet of Things (IoT) will all depend on embedded sensing of real-world phenomena, in-situ computation as well as automated information exchange and data distribution using machine-to-machine (M2M) com­munications between local and distributed control systems and machinery.

The ‘smart grid’ is one example of an application for future embedded systems, as it uses real-time sensing of the available renewable energy to determine where energy is to be routed across the power grid and controls intelligent machinery to increase production during peak times; this requires that internet-connected smart meters are installed in industrial plants and private homes alike to facilitate real-time sensing and control of technical systems.

Another exciting area of application for embedded systems is mobile and wearable technology, which allows users to access and manipulate information ‘on the go’ as the system provides relevant and timely information — indeed, this is one of the main purposes of mobile information technology such as smartphones and tablet computers. Additional meaning for this Human-Computer Interaction (HCI) is generated by the context of the device, the user, the location and many more factors, all of which are sensed and computed by a plenitude of embedded sensors and collocated or connected systems.

Wearable devices such as fitness trackers and smart watches collect bio-physiological and health-related data to facilitate novel applications, including smart contact lenses and feedback systems for the learning of physical activities. At the same time, increasing cross-device interoperability means that users of head-mounted augmented reality and virtual reality displays can, for instance, use their entire smartphone screen as a keyboard and have the typed text displayed on augmented reality glasses.

Programme content

The programme is divided into three module groups with core and elective modules. These are:

1. Human-Computer Interaction
2. Systems Engineering
3. Data Processing, Signals and Systems

Features

- Excellent rankings for computer science, e.g. in U-Multirank and the CHE rankings
- A strongly research-oriented two-year programme with a modern, broad range of subjects
- Allows flexible interest-based selection of modules from the groups ‘Human-Computer Interaction’, ‘Systems Engineering’ and ‘Data Processing, Signals and Systems’
- A fully English-taught programme
- An outstanding staff-student ratio
- Participation in cutting-edge research projects
- Excellent research and teaching infrastructure
- An extensive network of partnerships with academic institutions and businesses worldwide
- A great student experience in Passau, the ‘City of Three Rivers’

Language requirements

Unless English is your native language or the language of your secondary or undergraduate education, you should provide an English language certificate at level B2 CEFR, e.g. TOEFL with a minimum score of 567 PBT, 87 iBT or ITP 543 (silver); IELTS starting from 5.5; or an equivalent language certificate.

To facilitate daily life in Germany, it would be beneficial for you to have German language skills at level A1 CEFR (beginner’s level). If you do not have any German skills when starting out on the programme, you will complete a compulsory beginner’s German course during your first year of study.

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As a student of this master’s programme, you will develop a solid grasp of computer systems and networks through a broad, yet in-depth, training experience in the field of Computer Science and Engineering. Read more
As a student of this master’s programme, you will develop a solid grasp of computer systems and networks through a broad, yet in-depth, training experience in the field of Computer Science and Engineering.

You will acquire theoretical knowledge and engineering skills in:
Parallel and Distributed Systems
Computer Security and Dependability
Computer Systems Engineering
Communication Networks

Programme description

The programme instills a set of essential skills that prepare you to work in Information and Computing Technology (ICT).

Courses in Computer Networks, Fault Tolerant Computer Systems, Parallel and Distributed Systems, Computer Architecture, Computer Security, and Real-Time Systems are taught by internationally recognised faculty in Computer Science and Engineering. In addition to academic training in skills related to algorithm design, programming languages and computer systems engineering, you will gain hands-on experience with emerging technologies and have opportunities to participate in cutting-edge research.

This programme is the first within Chalmers to provide the necessary preparation to contribute to ubiquitous computing, cyber-physical systems, and other rapidly growing areas in the expanding ICT industry. If you are interested in becoming a technology expert in these and other areas, the programme provides excellent background for pursuing doctoral studies.

Why apply

You will learn the design methodologies used to construct computer systems and networks. Such methodologies include Fault-Tolerant Distributed Algorithm Design, Concurrent Programming, Computer Systems Engineering, Systems Programming, and Secure and Dependable Systems Design. The coursework is designed to develop both your theoretical knowledge and practical expertise.

For example, you will learn how to:

design a system based on new and existing components (Systems Engineering)
understand low-level hardware/software interaction, develop systems and applications (Programming)
analyse performance and system design limitations (Distributed Computing) and
assess, evaluate, and design systems, programs and applications to increase security and dependability (Systems Design).

Rather than concentrating on a single aspect of computer systems and networks, the courses provide the broad, practical and up-to-date experience required by major ICT companies who develop computer systems and networks.

Who should apply

The programme trains professionals in the field of Computer Science and Engineering. We welcome applications from graduates of Computer Science, Computer Engineering, Information Engineering, Software Engineering, Electrical Engineering, Mechatronics, Mathematics and Physics.

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