Individuals, governments and organizations now routinely connect their computers to the Internet to communicate, provide services, and access massive stores of shared information. These on-line activities, many conducted beyond national boundaries, have opened up enormous opportunities for security attacks such as identity thefts, computer hackings, privacy breaches, technical sabotages, etc. Addressing security threats and attacks in this vast and complex distributed environment is an immensely challenging task.
The Computer Security pathway is centred round a core Security theme that introduces students to fundamental security topics that arise in the design, analysis, and implementation of networked and distributed systems. Subsidiary themes allow students to investigate broader areas in which they may apply their newly acquired skills. The pathway is designed for students who wish to specialize in the security aspect of the Information Technology field.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The MSc in Advanced Computer Science has an excellent record of employment for its graduates. Opportunities exist in fields as diverse as finance, films and games, pharmaceuticals, healthcare, consumer products, and public services - virtually all areas of business and society. Manchester Computer Science MSc courses are considered among the best in the country and our graduates are actively targeted for the very top jobs in industry and academia.
Security plays a role in almost all areas where computers are being used, including, for example, finance, healthcare, consumer products, and public services. Thus students who have followed the Computer Security pathway will be ideally placed in any of these areas, especially in positions where they need to be aware of security issues and solutions.
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.
This programme is CEng accredited and fulfills the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
Are you interested in working with cutting-edge technology at the forefront of language processing?
MA Computational Linguistics is a course run by a leading research group at the University of Wolverhampton. As a Masters student on this course, you will be part of our Research Institute of Information and Language Processing (RIILP), an independent, research-driven University unit specialising in Linguistics and Natural Language Processing.
As the name suggests, Computational Linguistics (sometimes called Natural Language Processing) is the use of computers to study language. On the course, you will be able to study:
• How to use Python and the well-established NLTK library to process natural language texts;
• How to analyse real language usage;
• How to automatically translate text using computer programs;
• The use of computers to study features of language;
• Translation tools such as translation memory systems;
• Computer techniques for automatically classifying natural language texts;
• Understand how Siri, Amazon Echo and Google Home etc. work;
• How to design an experiment that will thoroughly test your research questions.
You will be mentored through this programme by experienced and leading academics from the field. Join our research group today to become part of this team of leading researchers and academics and create your path to a career in computers and language!
MA Computational Linguistics, when studied full-time, comprises of three semesters worth 60 credits each. Three modules will be studied in both Semester One and Semester Two. During the third semester, students will undertake their research project and complete a 15,000 word dissertation on any aspect of Computational Linguistics.
The course covers all aspects of Computational Linguistics in-line with current and leading work in research and industry, and is divided into the following taught modules:
1. Computer programming in Python
The students will be taught the Python computer programming language, which is specially designed for dealing with natural language texts.
2. Corpus Linguistics in R
Corpus Linguistics involves storing large amounts of text on the computer for linguistic analysis. R is a programming language used to study the statistics of language.
3. Machine translation and other natural language processing applications
The automatic translation of text using statistics. The members of the Research Group will each speak on their own research areas throughout the module.
4. Computational Linguistics
The use of computers to study language at all levels, such as relations between words, part of speech tagging, syntactic parsing and anaphora resolution.
5. Translation tools for professional translators
Using computer tools to speed up many aspects of translation, such as product manuals, film scripts, medical texts, video games and simultaneous interpreting.
6. Machine learning for language processing
Computer techniques for automatically classifying natural language texts, for NLP tasks such as making summaries of text automatically.
7. Research methods and professional skills
You will learn how to design an experiment to thoroughly test your research questions.
Translation Tools for Professional Translators is an elective module that may be chosen in the Second Semester to replace another taught module for those students who are interested in pursuing careers in Translation.
You will be expected to dedicate 9 hours per week to lectures and a proportionate amount of time to self-study and tutorials with your supervisor.
Opportunities:
- You will be taught by leading researchers in the field: our teaching staff at the Research Institute of Information and Language Processing (RIILP) are engaged in high-quality research, as evidenced by the latest RAE 2008 and REF 2014 results.
- We offer an exciting programme of invited lectures and research seminars, attended by both students and staff;
- The institute has a wide network of contacts in academia and in the industry from which you will be able to benefit.
The knowledge and skills developed in the course will be assessed in a variety of ways. Assessments will include writing assignments on given topics, reports on practical work carried out in the class, portfolios, projects, oral presentations, and tests.
The culmination of the study programme will be your 15,000-word dissertation, which will allow you to carry out an in-depth study of a chosen topic within the areas of corpus linguistics, language teaching, lexicography, or translation.
Graduates of this course will be well-placed to continue their academic/research careers by applying for PhD positions within RIILP or at other leading centres for language and information processing. This degree will also enable graduates to access research and development positions within the language processing and human language technology industries, as well as in related areas such as translation, software development and information and communication technologies, depending on their specific module choices and dissertation topic. It should be noted that computer programming is a skill that is increasingly sought after by many companies from technological backgrounds and skills gained from this course will place graduates in a good position to take up such posts. Past graduates from this course have also gone on to successful careers specifically within the computer programming industry.
The practical sessions include working with tools and software and developing programs based on the material taught in the lectures, allowing you to apply the technical skills you are learning. Some of the tasks are group based, feeding into the collaboration aspect of blended learning which enhances team-working skills, and some are done individually. Through portfolio building, you will be able to share your learning with other students. You will also be able to enhance your employability by sharing your online portfolio with prospective employers. Some assessments will require you to present your work to the rest of the class, enabling you to develop your presentation skills, which are useful in both academia and industry. Other transferrable skills are the abilities to structure your thoughts, present your ideas clearly in writing and prepare texts for a wider audience. You will acquire these skills through assessed report and essay writing, and most of all through writing your dissertation.
In the past twenty years, the Web has transformed society and changed the way we work, trade, learn, do science, organise our lives, and play. The Web is, on the one hand, a network of interlinked computers, protocols, and software and, on the other hand, a socio-cultural phenomenon that influences law, the media, business, science, etc. To shape and work with the current and future forms of the Web, we need to understand its underlying design principles and concepts, relevant issues and techniques, and how these interact and influence each other. The fast changing nature of the Web means that such a deep understanding is essential to understand the latest developments and their potential.
The Advanced Web Technologies pathway is centred around a core theme of the same name, Advanced Web Technologies, and combines it with a choice of closely related yet complimentary themes, including Software Engineering 1 & 2, Making Sense of Complex Data, and Learning from Data. Students following this theme will gain an understanding and insight into the technologies that deliver the Web as we see it today. The topics covered include underlying languages and standards used to represent information on the web; techniques for understanding and managing data and information in a web context; and techniques and technology used to design and deliver web infrastructure.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
Students following the Advanced Web Technologies 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 Wed infrastructure, ranging from the obvious Web developers and system providers to basically all companies employing or developing Web technologies.
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.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
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.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
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.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
It's relevant. Computers are a part of everything we do. The computer field drives innovation in many other fields, including medicine, education, business, communication, and entertainment.
It's creative and challenging. The variety of applications of computer science and engineering makes for highly-creative and challenging projects. Working in the computer field might mean building web-based applications, providing security for sensitive information, developing systems to process scientific data, writing software for new mobile devices, and much more.
It's lucrative. Jobs in the field are among the highest paid, in part because qualified computer scientists and engineers are in demand. The Bureau of Labor Statistics says computing is among the top fields for new job growth through 2018. Read the report...
The future is full of possibilities. There is no question computers are infiltrating every aspect of our society. With changing technology, we cannot know what exciting turns your career might take. What we can say is you will be in a position to contribute in whatever way you choose.
Our faculty is involved. UTC Computer Science students benefit from smaller classes and a low student/teacher ratio which means more interaction with your teachers. We have been where you are and understand that you need to be challenged and encouraged. All classes are taught by faculty with professional degrees. Most faculty hold the Ph.D. in Computer Science, Computer Engineering or a closely related discipline.
We prepare you for the real world. Our students have opportunities for internships, co-op experience and special projects within the College. This is part of why you'll find our graduates working for Fortune 500 companies, local, state and federal government agencies. They have also gone on to graduate programs in computer science, engineering, and medicine.
Don't take our word for it. Hear what Hope Wineman had to say about her choice of Computer Science and Engineering.
Computer Science: Computer Science
The CPSC M.S. program requires that a student completes a minimum of 33 semester hours in graduate work including the thesis, or 36 semester hours in graduate work including a graduate project. Students admitted to the program who lack academic experience in certain areas will be assigned up to 18 hours of additional course work in the foundation courses listed below in order to gain needed competencies. All students admitted to the M.S. program must complete 15 semester hours of required course in the core courses listed below. The program also includes 6 hours of thesis, 9 hours of computer science elective courses and additional 3 hours of coursework related to the student’s objectives may be selected from an area within or outside of computer science, in consultation with the major adviser and the Graduate Coordinator. Students may elect to undertake a project in lieu of a thesis. In this case, 6 additional hours of elective coursework, for a minimum total of 36 hours of graduate credit, are required. The courses used for these additional six hours are subject to the approval of the major adviser and the Graduate Coordinator of Computer Science. With either the thesis or project option, a minimum of 21 hours of credit must be from UTC computer science courses at the 5000 level. Students must maintain a minimum 3.0 grade point average and are subject to all general regulations of The Graduate School, such as those regulating admission to candidacy, transfer of credits, time limitations, thesis, and degree conferral.
Computer Science: Data Science
Information on the Data Science concentration can be found here.
Computer Science: Information Security and Assurance
The CPSC-ISA M.S. program requires that a student completes a minimum of 33 semester hours in graduate work including the thesis, or 36 semester hours in graduate work including a graduate project. Students admitted to the program who lack academic experience in certain areas will be assigned up to 18 hours of additional course work in the foundation courses listed below in order to gain needed competencies. All students admitted to the M.S. program must complete 15 semester hours of required course in the computer science core courses and 6 semester hours of required course in ISA core courses listed below. The program also includes 6 hours of thesis, 3 hours of ISA elective courses and additional 3 hours of coursework related to the student’s objectives may be selected from an area within or outside of computer science, in consultation with the major adviser and the Graduate Coordinator. Students may elect to undertake a project in lieu of a thesis. In this case, 3 additional hours of ISA elective coursework and 3 additional hours of elective course, for a minimum total of 36 hours of graduate credit, are required. The courses used for these additional 3 elective hours are subject to the approval of the major adviser and the Graduate Coordinator. With either the thesis or project option, a minimum of 21 hours of credit must be from UTC computer science courses at the 5000 level. Students must maintain a minimum 3.0 grade point average and are subject to all general regulations of The Graduate School, such as those regulating admission to candidacy, transfer of credits, time limitations, thesis, and degree conferral.
Our computer science conversion course is for those who have little or no experience in computing. You will study the principles and practice of computing. It will include the fundamentals of computing science, database design, network technologies and programming.
This course can also be taken as Continuing Professional Development (CPD), for example by ICT teachers who are switching to the new Computer Science curriculum.
Our graduates have an excellent record of finding employment (around 90%). Recent examples include:
-Graduate Trainee, British Airways
-Software Developer, IBM UK
-Graduate Developer, Scott Logic
-Software Engineer, BT
Our research expertise feeds into our teaching. This means that you learn at the cutting edge of the discipline. We incorporate new techniques and knowledge into your learning and have an active research community. We have several research groups and four three research centres.
The course is delivered by the School of Computing. You can study over one year full time or two years' part time.
The first nine months of the full time course are devoted to taught modules (120 credits), which are examined by written papers. There will be about 20 contact hours per week. You will also undertake a substantial amount of supervised and unsupervised practical work.
The taught part of the course follows three main threads:
The three summer months are devoted to a dissertation project (worth 60 credits).
You can find more information on the School website:
We seek British Computer Society (BCS) accreditation for all our degrees. This ensures that you will graduate with a degree that meets the standards set out by the IT industry. A BCS-accredited degree provides the foundation for professional membership of the BCS on graduation. This is the first step to becoming a chartered IT professional.
The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.
You will have dedicated computing facilities in the School of Computing. You will have access to the latest tools for system analysis and development. For certain projects, special facilities for networking can be set up.
You will enjoy access to specialist IT facilities to support your studies, including:
We have moved to the new £58m purpose-built Urban Sciences Building. Our new building offers fantastic new facilities for our students and academic community. The building is part of Science Central, a £350 million project bringing together:
This is a high quality course aimed at imparting advanced knowledge across a broad range of Computer Science and offering training in advanced skills. It is suitable for those who wish to enhance their computing skills in order to improve their contribution to IT-related industry or to pursue R&D in academia or industry.
A student following the Advanced Computer Science course chooses two from about a dozen themes, each of which combines two related course units that build on top of each other. Certain combinations are integrated into specialised 'pathways' . A student who opts to follow the pathways will have the pathway specialism included in their degree certificate.
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.
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.
A student following the Advanced Computer Science course chooses two from about a dozen themes, each of which combines around four related course units that build on top of each other. Certain combinations are integrated into specialised pathways
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The MSc in Advanced Computer Science has an excellent record of employment for its graduates. Opportunities exist in fields as diverse as finance, films and games, pharmaceuticals, healthcare, consumer products, and public services - virtually all areas of business and society. Our courses are considered among the best in the country and our graduates are actively targeted for the very top jobs in industry and academia. The MSc is also a route to further study at research level, or to careers in industrial or academic research.
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.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.
Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.
Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.
Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?
This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.
Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 60 full-time academic staff.
- In the latest independent Research Assessment Exercise, the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).
Advanced Techniques for Differential Equations
Computational Linear Algebra
Operations Research and Modelling
Programming for Scientific Computation
Scientific Computation Dissertation
Simulation for Computer Scientists
Stochastic Financial Modelling
Variational Methods
Vocational Mathematics
Data Mining Techniques and Applications
Mathematical Foundations of Programming
IELTS: 6.0 (with no less than 5.5 in any element)
Our Medical Physics MSc programme is well-established and internationally renowned. We are accredited by IPEM (Institute of Physics and Engineering in Medicine) and we have trained some 1,000 medical physicists, so you can look forward to high-quality teaching during your time at Surrey.
The syllabus for the MSc in Medical Physics is designed to provide the knowledge, skills and experience required for a modern graduate medical physicist, placing more emphasis than many other courses on topics beyond ionising radiation (X-rays and radiotherapy).
Examples of other topics include magnetic resonance imaging and the use of lasers in medicine.
You will learn the theoretical foundations underpinning modern imaging and treatment modalities, and will gain a set of experimental skills essential in a modern medical physicist’s job.
These skills are gained through experimental sessions in the physics department and practical experiences at collaborating hospitals using state-of-the-art clinical facilities.
Why not discover more about our programme in our video?
This programme is studied full-time over one academic year. It consists of eight taught modules and a dissertation project. Part-time studemts study the same content over 2 academic years.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that all modules are compulsory, there are no optional modules, and may be subject to change.
Common room
A student common room is available for the use of all Physics students.
Computers
The University has an extensive range of PC and UNIX machines, full internet access and email. The University has invested in resources to allow students to develop their IT skills. It also has an online learning environment, SurreyLearn. Computers are located in dedicated computer rooms. Access to these rooms is available 24 hours per day.
Hounsfield Prize
A prize of £200 is awarded annually for the best dissertation on the Medical Physics programme. Sir Hounsfield was jointly awarded the Nobel Prize for Medicine in 1979 for his work on Computed Tomography.
Mayneord Prize
A prize of £200 in memory of Professor Valentine Mayneord will be awarded to the student with the best overall performance on the Medical Physics course. Professor Mayneord was one of the pioneers of medical physics, who had a long association with the Department and encouraged the growth of teaching and research in the field.
Knoll Prize
A prize of £300 in memory of Professor Glenn Knoll is awarded annually to the student with outstanding performance in Radiation Physics and Radiation Measurement on any of the department's MSc programmes. Professor Knoll was a world-leading authority in radiation detection, with a long association with the department
IPEM Student Prize (MSc Medical Physics)
A prize of £250 is awarded annually to a student with outstanding performance in their dissertation.
The programme integrates the acquisition of core scientific knowledge with the development of key practical skills with a focus on professional career development within medical physics and related industries. The principle educational aims and outcomes of learning are to provide participants with advanced knowledge, practical skills and understanding applied to medical physics, radiation detection instrumentation, radiation and environmental practice in an industrial or medical context. This is achieved by the development of the participants’ understanding of the underlying science and technology and by the participants gaining an understanding of the legal basis, practical implementation and organisational basis of medical physics and radiation measurement.
We give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities and through our international research collaboration. Hence, it may be possible to carry out the dissertation project abroad.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
Computer Systems Engineering is a well-established branch of Computer Science, closely related to Electrical Engineering, and concerned with software-hardware integration and the development of high-performance and energy-efficient embedded systems, for example as used in mobile computing. Aspects covered include questions such as how software can be designed to make use of new, ever more powerful (and often multicore) hardware, or how hardware can be designed to support certain software paradigms. The School of Computer Science is home to internationally renowned research groups working on these challenging tasks, and students following the Computer Systems Engineering pathway will have the opportunity to profit from their understanding of current technology and visions of how to exploit, for example, the formidable complexity of the billion transistor microchips that semiconductor technology will make commonplace over the next decade.
This pathway combines two themes, namely the Parallel Computing in the Mulit-core Era theme and the Mobile Computing theme. The former provides the student with techniques and tools to successfully develop concurrent multicore systems, while alleviating problems of correctness, reliability, performance and system management. The latter provides the student with an understanding of the current state of the art in computing to support mobility for telecommunications.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The MSc in Advanced Computer Science has an excellent record of employment for its graduates. Opportunities exist in fields as diverse as finance, films and games, pharmaceuticals, healthcare, consumer products, and public services - virtually all areas of business and society. Manchester Computer Science MSc courses are considered among the best in the country and our graduates are actively targeted for the very top jobs in industry and academia.
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.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
Efficient management of data and knowledge are key factors not only to the success of almost any enterprise, but also to the successful handling of today's vast amounts of science related data: with the transition to the information age and the knowledge economy, data has become both increasingly central and critical to all activities. For example, imagine the huge amounts of genomic or patient data available electronically, and how the quality of their management can affect society.
The Data and Knowledge Management pathway allows students to take specialist themes concerned with methods and technologies for the adequate management of data and knowledge. The Managing Data theme focuses on the design, maintenance, and query processing of both structured and unstructured databases. The Learning from Data theme covers principles, algorithms, and technologies underlying machine learning, probabilistic modelling, and optimisation, while exposing students to relevant applications. The Advanced Web Technologies theme provides students with a deep understanding of the technologies that are being used to support the continuing evolution of the Web, including Semantic Web technologies.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
Students following the Data and Knowlege Management 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 data and knowledge management tools and technologies. This includes data and knowledge engineering positions in all areas where data is stored and managed electronically, i.e., in all areas, including the finance, retail, and healthcare sector.
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.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
These are exciting times in biology and medicine. The genomics revolution is opening up whole new areas of research - from new insights into how organisms function, to new understandings of disease and disease processes. Medicine is currently involved in the largest and most ambitious IT project in the world - the capture and interpretation of electronic patient records. This information will make health care much more effective and can help spot new diseases early - whilst they can still be contained and controlled. At the heart of all these developments are data and knowledge - and a real need and demand for the skills and techniques that computer scientists can bring these problem areas. Biology and healthcare now provide some of the fastest growing and most challenging areas for computer scientists to apply their skills.
The Digital Biology pathway is centered around a central theme of Biohealth Informatics. The theme is specifically designed for computer scientists without any previous experience of medicine or biology and will help you to develop the core skills needed to work or research (as a computer scientist) in these rapidly evolving fields. This core theme is complemented by a range of other themes that allow students to develop additional skills which have important applications in healthcare and biology.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
Students following the Digital Biology pathway have all the career options as described for general Advanced Computer Science.
In addition, students following this pathway are well placed for careers with healthcare providers, the pharmaceutical industry, and bio-health research institutes.
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.
This programme is CEng accredited and fulfills the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.
Semantic Technologies is a relatively new term that describes all areas concerned with using and developing software and methodologies for meaning-centred manipulation of information. The aim is to provide software and methodologies so that web resources, data in databases and raw data associated with programs can be processed and manipulated in a more intelligent way. This requires storing, understanding, manipulating and reasoning about the meaning of the data. Semantic technologies are increasingly being used in such varied applications as the semantic web, health care and biomedical domains, the life sciences, software/hardware industries and the automotive industry.
The Semantic Technologies pathway combines themes such as 'Data on the Web' with 'Ontology Engineering and Automated Reasoning'. These core offerings can be combined with any other theme. Good complementary themes are Data Engineering, Managing Data, Learning from Data, Security and Software Engineering.
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.
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.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
Students following the Semantic Technologies 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 software companies or for healthcare providers who are using or developing Semantic Technologies.
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.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with a CEng accredited Bachelors programme.
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