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Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences. Read more
Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences.

The course is aimed at introducing students to quantitative aspects of biological and medical sciences. It is intended for mathematicians, computer scientists and others wishing to learn about the subject in preparation for a PhD course or a career in industry. It is also suitable for students with a first degree in biosciences as long as they have strong quantitative skills (which should be documented in the application).

This 11-month course consists of core modules in bioinformatics, scientific programming with R, genomics, systems biology and network biology. Before the start of the first term, students are required to attend an introductory course in molecular biology. Courses are delivered in association with several University departments from the Schools of Biological Sciences and Physical Sciences, groups within the School of Clinical Medicine, the European Bioinformatics Institute and the Sanger Institute. The course concludes with a three-month internship in a university or industrial laboratory.

Visit the website: http://www.graduate.study.cam.ac.uk/courses/directory/maammpcbi

Learning Outcomes

After completing the MPhil in Computational Biology, students will be expected to have:

- acquired a sound knowledge of a range of tools and methods in computational biology;
- developed the capacity for independent study and problem solving at a higher level;
- undertaken an internship project within a laboratory or group environment, and produced a project report;
- given at least one presentation on their project.

Format

The course combines taught lectures (October-April), followed by a summer internship project (May-August). There are typically 3-4 taught modules per term, and each module consists of 16 hours of lectures. Each module is assessed by coursework, and there is one general examination in May.

The Course Director is available throughout the year for individual meetings, and briefly meets termly with each student to check on progress. Each lecturer is also encouraged to arrange an office hour whereby students can talk about their progress.

Lectures: Typically 16 hours per module, with students taking 8 modules.

Journal Clubs: A weekly seminar is held during the first two terms on topics across Computational Biology. These seminars help students to select an appropriate project.

Placements

Students undertake a mandatory internship (May to August) in either a university or industrial laboratory. The Department will compile a list of possible opportunities which students can discuss directly with the host laboratory. Alternatively students may organise their own internship, subject to the approval of the Course Director.

Assessment

A 18,000 word (maximum) report must be written to summarise the student's internship. An oral presentation on this report must also be given.

Students give a 25 minute presentation on their project as part of the formal assessment. Some assessed coursework may also require students to present their work.

Each module is assessed typically by two written assignments. These assignments involve significant computational elements.

A compulsory two-hour general examination is sat in May.

Continuing

MPhil students wishing to apply for a PhD at Cambridge must apply via the Graduate Admissions Office for continuation by the relevant deadline.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities: http://www.2016.graduate.study.cam.ac.uk/finance/funding

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Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences. Read more
Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences.

The course is aimed at introducing students to quantitative aspects of biological and medical sciences. It is intended for mathematicians, computer scientists and others wishing to learn about the subject in preparation for a PhD course or a career in industry. It is also suitable for students with a first degree in biosciences as long as they have strong quantitative skills (which should be documented in the application).

This 11-month course consists of core modules in bioinformatics, scientific programming with R, genomics, systems biology and network biology. Before the start of the first term, students are required to attend an introductory course in molecular biology. Courses are delivered in association with several University departments from the Schools of Biological Sciences and Physical Sciences, groups within the School of Clinical Medicine, the European Bioinformatics Institute and the Sanger Institute. The course concludes with a three-month internship in a university or industrial laboratory.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/maammpcbi

Course detail

After completing the MPhil in Computational Biology, students will be expected to have:

- acquired a sound knowledge of a range of tools and methods in computational biology;
- developed the capacity for independent study and problem solving at a higher level;
- undertaken an internship project within a laboratory or group environment, and produced a project report;
- given at least one presentation on their project.

Format

The course combines taught lectures (October-April), followed by a summer internship project (May-August). There are typically 3-4 taught modules per term, and each module consists of 16 hours of lectures. Each module is assessed by coursework, and there is one general examination in May.

Placements

Students undertake a mandatory internship (May to August) in either a university or industrial laboratory. The Department will compile a list of possible opportunities which students can discuss directly with the host laboratory. Alternatively students may organise their own internship, subject to the approval of the Course Director.

Assessment

A 18,000 word (maximum) report must be written to summarise the student's internship. An oral presentation on this report must also be given.

Each module is assessed typically by two written assignments. These assignments involve significant computational elements.

A compulsory two-hour general examination is sat in May.

Continuing

MPhil students wishing to apply for a PhD at Cambridge must apply via the Graduate Admissions Office for continuation by the relevant deadline.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. Read more

Research profile

The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.

We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.

Our research falls into three areas:

-machine learning
-computational neuroscience
-computational biology

In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.

In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments

The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).

Training and support

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

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

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

Facilities

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

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

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

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

Career opportunities

The research you will undertake at IANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.

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The MSc in Bioinformatics and Computational Biology at UCC is a one-year taught masters course commencing in September. Bioinformatics is a fast-growing field at the intersection of biology, mathematics and computer science. Read more
The MSc in Bioinformatics and Computational Biology at UCC is a one-year taught masters course commencing in September. Bioinformatics is a fast-growing field at the intersection of biology, mathematics and computer science. It seeks to create, advance and apply computer/software-based solutions to solve formal and practical problems arising from the management and analysis of very large biological data sets. Applications include genome sequence analysis such as the human genome, the human microbiome, analysis of genetic variation within populations and analysis of gene expression patterns.

As part of the MSc course, you will carry out a three month research project in a research group in UCC or in an external university, research institute or industry. The programming and data handling skills that you will develop, along with your exposure to an interdisciplinary research environment, will be very attractive to employers. Graduates from the MSc will have a variety of career options including working in a research group in a university or research institute, industrial research, or pursuing a PhD.

Visit the website: http://www.ucc.ie/en/ckr33/

Course Detail

This MSc course will provide theoretical education along with practical training to students who already have a BSc in a biological/life science, computer science, mathematics, statistics, engineering or a related degree.

The course has four different streams for biology, mathematics, statistics and computer science graduates. Graduates of related disciplines, such as engineering, physics, medicine, will be enrolled in the most appropriate stream. This allows graduates from different backgrounds to increase their knowledge and skills in areas in which they have not previously studied, with particular emphasis on hands-on expertise relevant to bioinformatics:

- Data analysis: basic statistical concepts, probability, multivariate analysis methods
- Programming/computing: hands-on Linux skills, basic computing skills and databases, computer system organisation, analysis of simple data structures and algorithms, programming concepts and practice, web applications programming
- Bioinformatics: homology searches, sequence alignment, motifs, phylogenetics, protein folding and structure prediction
- Systems biology: genome sequencing projects and genome analysis, functional genomics, metabolome modelling, regulatory networks, interactome, enzymes and pathways
- Mathematical modelling and simulation: use of discrete mathematics for bioinformatics such as graphs and trees, simulation of biosystems
- Research skills: individual research project, involving a placement within the university or in external research institutes, universities or industry.

Format

Full-time students must complete 12 taught modules and undertake a research project. Part-time students complete about six taught modules in each academic year and undertake the project in the second academic year. Each taught module consists of approximately 20 one-hour lectures (roughly two lectures per week over one academic term), as well as approximately 10 hours of practicals or tutorials (roughly one one-hour practical or tutorial per week over one academic term), although the exact amount of lectures, practicals and tutorials varies between individual modules.

Assessment

There are exams for most of the taught modules in May of each of the two academic years, while certain modules may also have a continuous assessment element. The research project starts in June and finishes towards the end of September. Part-time students will carry out their research project during the summer of their second academic year.

Careers

Graduates of this course offer a unique set of interdisciplinary skills making them highly attractive to employers at universities, research centres and in industry. Many research institutes have dedicated bioinformatics groups, while many 'wet biology' research groups employ bioinformaticians to help with data analyses and other bioinformatics problems. Industries employing bioinformaticians include the pharmaceutical industry, agricultural and biotechnology companies. For biology graduates returning to 'wet lab' biology after completing the MSc course, your newly acquired skills will be extremely useful. Non-biology graduates seeking non-biology positions will also find that having acquired interdisciplinary skills is of great benefit in getting a job.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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Research in the School of Biosciences revolves around understanding systems and processes in the living cell. It has a strong molecular focus with leading-edge activities that are synergistic with one another and complementary to the teaching provision. Read more
Research in the School of Biosciences revolves around understanding systems and processes in the living cell. It has a strong molecular focus with leading-edge activities that are synergistic with one another and complementary to the teaching provision.

Our expertise in disciplines such as biochemistry, microbiology and biomedical science allow us to exploit technology and develop ground-breaking ideas in the fields of genetics, molecular biology, protein science, biophysics and computational biology. Fields of enquiry encompass a range of molecular processes from cell division, transcription and translation through to molecular motors, molecular diagnostics and the production of biotherapeutics and bioenergy.

Our research degrees are based around lab-based and computational research projects. The MSc is a one year full-time programme (two years part-time).

In all our research degrees you undertake a single, focused, research project from day one, and attend only certain components of our transferable skills modules. You are supervised by a team which comprises your main supervisor(s) as well as supervisory chairs that give independent advice on progression.

Visit the website https://www.kent.ac.uk/courses/postgraduate/apply-online/1237

About the School of Biosciences

The School of Biosciences is among the best-funded schools of its kind in the UK, with current support from the BBSRC, NERC, MRC, Wellcome Trust, EU, and industry. It has 38 academic staff, 56 research staff (facility managers, research fellows, postdoctoral researchers and technicians), approximately 100 postgraduate research students and 20 key support staff. The school's vibrant atmosphere has expanded to become a flourishing environment to study for postgraduate degrees in a notably friendly and supportive teaching and research environment.

In addition to research degrees, our key research strengths underpin a range of unique and career-focused taught Master’s programmes that address key issues and challenges within the biosciences and pharmaceutical industries and prepare graduates for future employment.

Research areas

Research in the School of Biosciences is focused primarily on essential biological processes at the molecular and cellular level, encompassing the disciplines of biochemistry, genetics, biotechnology and biomedical research.

The School’s research has three main themes:

- Protein Science – encompasses researchers involved in industrial biotechnology and synthetic biology, and protein form and function

- Molecular Microbiology – encompasses researchers interested in yeast molecular biology (incorporating the Kent Fungal Group) and microbial pathogenesis

- Biomolecular Medicine – encompasses researchers involved in cell biology, cancer targets and therapies and cytogenomics and bioinformatics.

Each area is led by a senior professor and underpinned by excellent research facilities. The School-led development of the Industrial Biotechnology Centre (IBC), with staff from the other four other schools in the Faculty of Sciences, facilitates and encourages interdisciplinary projects. The School has a strong commitment to translational research, impact and industrial application with a substantial portfolio of enterprise activity and expertise.

Careers

A postgraduate degree in the School of Biosciences is designed to equip our graduates with transferable skills that are highly valued in the workplace. Our research-led ethos ensures that students explore the frontiers of scientific knowledge, and the intensive practical components provide rigorous training in cutting edge technical skills that are used in the modern biosciences while working in areas of world-leading expertise within the School.

Destinations for our graduates include the leading pharmaceutical and biotechnological companies within the UK and leading research institutes both at home and abroad.

Find out how to apply here -

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Modern biotechnology is a hugely complex subject, and this course covers its key areas, helping you develop an advanced understanding of molecular and computational biology through to applied microbiology. Read more
Modern biotechnology is a hugely complex subject, and this course covers its key areas, helping you develop an advanced understanding of molecular and computational biology through to applied microbiology.

You will learn about the latest new technologies in these three areas, gain insights into how they are used in the global biotechnology industry, and discover how microbes can be used on an industrial scale to benefit humankind.

Visit the website: https://www.beds.ac.uk/howtoapply/courses/postgraduate/next-year/biotechnology

Course detail

• Study the latest developments in applied microbiology and computational biology in high-quality, broad-based classes taught by dedicated staff with research experience in specialist subject areas
• Explore the latest technologies in molecular biology and the industrial processes that are used to exploit microbes for specific products and applications
• Develop the ability to use information from relevant sources, and independently and critically evaluate current research and advanced scholarship
• Gain the ability to use assured, accurate and fluent language to present your work, and learn to develop graphs and images that clearly illustrate complex points
• Benefit from a wide knowledge base and the key transferable skills that will give you the opportunity to take your career to new heights.

Modules

• Molecular Biology
• Computational Biology
• Analytical Methods
• Applied Microbiology
• Laboratory Based Research Project (Biotechnology)

Assessment

Assessment is undertaken in all units of the course to check that you have met (or are working towards meeting) the threshold standards expected of all students.

Each unit of study has three summative assessment points and when each is marked you will be provided with feedback that is designed to show you where you are meeting/exceeding the standards and where/how you can/should make further improvement.

Careers

In addition to developing your specialist knowledge and understanding, there is emphasis on developing your approach and attitude to working by emphasising and encouraging the professional standards expected by employers. This is supported by a departmental seminar programme that includes speakers from industry who will give you an insight into what they expect from employees.

The University also has a programme of seminars and workshops designed to help you recognise and boost the attributes expected and appreciated by employers. This is supplemented by trips and visits.

Funding

For information on available funding, please follow the link: https://www.beds.ac.uk/howtoapply/money/scholarships/pg

How to apply

For information on how to apply, please follow the link: https://www.beds.ac.uk/howtoapply/course/applicationform

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This course provides specialist skills in core systems biology with a focus on the development of computational and mathematical research skills. Read more
This course provides specialist skills in core systems biology with a focus on the development of computational and mathematical research skills. It specialises in computational design, providing essential computing and engineering skills that allow you to develop software to program biological systems.

This interdisciplinary course is based in the School of Computing Science and taught jointly with the Faculty of Medical Sciences and the School of Mathematics and Statistics. The course is ideal for students aiming for careers in industry or academia. We cater for students with a range of backgrounds, including Life Sciences, Computing Science, Mathematics and Engineering.

Computational Systems Biology is focused on the study of organisms from a holistic perspective. Computational design of biological systems is essential for allowing the construction of complex and large biological systems.

We provide a unique, multidisciplinary experience essential for understanding systems biology. The course draws together the highly-rated teaching and research expertise of our Schools of Computing Science, Mathematics and Statistics, Biology, and Cell and Molecular Biosciences. The course also has strong links with Newcastle's Centre for Integrated Systems Biology of Ageing and Nutrition (CISBAN).

Our course is designed for students from both biological and computational backgrounds. Prior experience with computers or computer programming is not required. Students with mathematical, engineering or other scientific backgrounds are also welcome to apply.

The course is part of a suite of related programmes that also include:
-Bioinformatics MSc
-Synthetic Biology MSc
-Computational Neuroscience and Neuroinformatics MSc

All four programmes share core modules, creating a tight-knit cohort. This encourages collaborations on projects undertaking interdisciplinary research.

Project work

Your five month research project gives you a real opportunity to develop your knowledge and skills in depth in Systems Biology. You have the opportunity to work closely with a leading research team in the School and there are opportunities to work on industry lead projects. You will have one-to-one supervision from an experienced member of the faculty, supported with supervision from associated senior researchers and industry partners as required.

The project can be carried out:
-With a research group at Newcastle University
-With an industrial sponsor
-With a research institute
-At your place of work

Placements

Students have a unique opportunity to complete a work placement with one of our industrial partners as part of their projects.

Previous students have found placements with organisations including:
-NHS Business Services Authority
-Waterstons
-Metropolitan Police
-Accenture
-IBM
-Network Rail
-Nissan
-GSK

Accreditation

We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and 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.

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This interdisciplinary Masters degree combines teaching and research from the School of Mathematics and the School of Computing. You will be introduced to sophisticated techniques at the forefront of mathematics and computer science. Read more
This interdisciplinary Masters degree combines teaching and research from the School of Mathematics and the School of Computing. You will be introduced to sophisticated techniques at the forefront of mathematics and computer science. Based on the Schools’ complementary research strengths the programme follows two main strands:

Algorithms & Complexity Theory
This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty.

This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology.

Numerical Methods & Parallel Computing
Many problems, in maths, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled to the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has many applications, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more.

This MSc will provide you with technical and transferable skills that are valued by industry.

You will gain key algorithmic tools to work across many industries including transport infrastructure, health informatics, computational biology, artificial intelligence, companies developing the internet e.g. search engines.

You could also progress onto a career in computing or finance where mathematics is valued.

It will also provide you with an excellent background if you wish to embark on a PhD in mathematics or in computer science.

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The field of Ecology, Evolution and Development describes how the molecular and genetic regulation of development changes in response to evolutionary forces to generate organismal diversity. Read more
The field of Ecology, Evolution and Development describes how the molecular and genetic regulation of development changes in response to evolutionary forces to generate organismal diversity. Understanding development, and its regulation in ecological and evolutionary contexts is critical for developing emerging molecular medical techniques, understanding biodiversity and tracing evolution.

See the website http://www.brookes.ac.uk/courses/postgraduate/ecology-evolution-and-development/

Why choose this course?

- Development of interdisciplinary research skills and experience.

- Opportunity to carry out an in-depth research project to address open questions in this field.

- Hands-on research driven training in field work, advanced wet laboratory techniques and state-of-the-art bioinformatics.

- Intensive one week introductory workshop for students from all backgrounds.

- Enhanced ability of graduates to successfully compete for PhD positions in the UK and internationally.

- Training will provide skills that will increase the employability of graduates in the biotechnology, commercial and health sectors.

- Teaching by world class researchers in this field with recognised excellence and experience in teaching and learning.

Teaching and learning

Teaching and learning methods used in the course reflect the wide variety of topics and techniques associated with ecology, evolution and development.

- Structure
This course is designed to provide you with both the conceptual framework of this interdisciplinary field and develop practical and academic skills as a platform for the research project. An intensive one week Research Methods module will introduce you to key topics and practical approaches. These are then elaborated on during the three other taught modules in Developmental Biology, Bioinformatics, and Molecular Ecology and Population Genetics, before the students embark on the research project. A variety of teaching and learning methods are employed in this course, all underpinned by research.

- Lectures
By providing the framework, essential background and knowledge base for each module, the lectures encourage you to probe more deeply by reading widely. Analysis, synthesis and application of material introduced in lectures are achieved through practical work in the field and laboratories, and in tutorials and seminars with your tutors and fellow students.

- Practical work
This offers you training and hands-on experience in important aspects of field and laboratory work, and computational biology. We ensure that teaching is up-to-date by integrating research findings in lectures and practical classes, and staff involved with major international developments in the field bring these advances to your teaching. An important component of the course is that you read and present key papers that emphasise the application of interdisciplinary approaches to their tutor and peers during tutorials.

- Guest seminars
During the Research Methods module, guest seminars provide you with the chance to hear about other areas of research in ecology, evolution and development. Emphasis is placed on critical evaluation of existing information and identifying knowledge gaps and areas of controversy, fostering the development of academic and research literacy, and developing your critical self-awareness.

- Research project
Standards that are expected in research are also widely taught and practised, developing your research literacy. You are provided with the opportunity to undertake substantial research specific activities in the Research Module, and undertake projects in labs with active research in this field.

- Digital literacy
This is enhanced by the use of advanced information retrieval techniques, data handling and the development of professional presentation techniques. Furthermore, you will develop skills in programming which underpin the application of state-of-the-art tools in bioinformatics and biostatistics.

How this course helps you develop

Training provided by this course will give you the research and transferable skills necessary for further research in field, lab and computational biology in both academic and industrial sectors. We anticipate that many of our graduates will go on to study for PhDs in the UK and abroad. In this respect, our programme will increase the opportunities for UK graduates to compete for PhD positions here and be eligible to apply for PhD programmes elsewhere in the EU. We also anticipate that, given their skills sets, our graduates will be highly competitive for employment in research support and sales, biotechnology, heath care, education, administration, and consultancy.

Careers

- PhD
- Employment in others sectors including biotechnology, healthcare and commercial.

Free language courses for students - the Open Module

Free language courses are available to full-time undergraduate and postgraduate students on many of our courses, and can be taken as a credit on some courses.

Please note that the free language courses are not available if you are:
- studying at a Brookes partner college
- studying on any of our teacher education courses or postgraduate education courses.

Research highlights

In the Research Excellence Framework (REF) 2014, 95% of our research in Biological Sciences was rated as internationally recognised, with 58% being world leading or internationally excellent. That makes us the top post’92 University for its Biological Sciences submission.

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The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. Read more

Mathematical Biology at Dundee

The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. In his famous book On Growth and Form (where he applied geometric principles to morphological problems) Thompson declares:

"Cell and tissue, shell and bone, leaf and flower, are so many portions of matter, and it is in obedience to the laws of physics that their particles have been moved, molded and conformed. They are no exceptions to the rule that God always geometrizes. Their problems of form are in the first instance mathematical problems, their problems of growth are essentially physical problems, and the morphologist is, ipso facto, a student of physical science."

Current mathematical biology research in Dundee continues in the spirit of D'Arcy Thompson with the application of modern applied mathematics and computational modelling to a range of biological processes involving many different but inter-connected phenomena that occur at different spatial and temporal scales. Specific areas of application are to cancer growth and treatment, ecological models, fungal growth and biofilms. The overall common theme of all the mathematical biology research may be termed"multi-scale mathematical modelling" or, from a biological perspective, "quantitative systems biology" or"quantitative integrative biology".

The Mathematical Biology Research Group currently consists of Professor Mark Chaplain, Dr. Fordyce Davidson and Dr. Paul Macklin along with post-doctoral research assistants and PhD students. Professor Ping Lin provides expertise in the area of computational numerical analysis. The group will shortly be augmented by the arrival of a new Chair in Mathematical Biology (a joint Mathematics/Life Sciences appointment).

As a result, the students will benefit directly not only from the scientific expertise of the above internationally recognized researchers, but also through a wide-range of research activities such as journal clubs and research seminars.

Aims of the programme

1. To provide a Masters-level postgraduate education in the knowledge, skills and understanding of mathematical biology.
2. To enhance analytical and critical abilities and competence in the application of mathematical modeling techniques to problems in biomedicine.

Prramme Content

This one year course involves taking four taught modules in semester 1 (September-December), followed by a further 4 taught modules in semester 2 (January-May), and undertaking a project over the Summer (May-August).

A typical selection of taught modules would be:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Personal Transferable Skills

Finally, all students will undertake a Personal Research Project under the supervision of a member of staff in the Mathematical Biology Research Group.

Methods of Teaching

The programme will involve a variety of teaching formats including lectures, tutorials, seminars, journal clubs, case studies, coursework, and an individual research project.

Taught sessions will be supported by individual reading and study.

Students will be guided to prepare their research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

Career Prospects

The Biomedical Sciences are now recognizing the need for quantitative, predictive approaches to their traditional qualitative subject areas. Healthcare and Biotechnology are still fast-growing industries in UK, Europe and Worldwide. New start-up companies and large-scale government investment are also opening up employment prospects in emerging economies such as Singapore, China and India.

Students graduating from this programme would be very well placed to take advantage of these global opportunities.

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This course provides you with a balance of molecular biology, engineering, computing and modelling skills necessary for a career in synthetic biology. Read more
This course provides you with a balance of molecular biology, engineering, computing and modelling skills necessary for a career in synthetic biology. Computational design of biological systems is important as the field of synthetic biology grows. This allows the construction of complex and large biological systems.

While laboratory approaches to engineering biological systems are a major focus, the course specialises in computational design. This provides you with essential computing and engineering skills to allow you to develop software to program biological systems.

Our course is designed for students from both biological and computational backgrounds. Prior experience with computers or computer programming is not required. Students with mathematical, engineering or other scientific backgrounds are also welcome to apply. It is ideal if you are aiming for careers in industry or academia.

We provide a unique, multidisciplinary experience that is essential for understanding synthetic biology. The programme draws together the highly-rated teaching and research expertise of our Schools of Computing Science, Mathematics and Statistics, and Biology, as well as the Medical Faculty and the Institute of Human Genetics.

Research is a large component of this course. The emphasis is on delivering the research training you will need in the future to meet the demands of industry and academia effectively. Newcastle's research in life sciences, computing and mathematics is internationally recognised.

The teaching staff are successful researchers in their field and publish regularly in highly-ranked systems synthetic biology journals.

Our experienced and friendly staff are on hand to help you. You gain the experience of working in a team in an environment with the help, support and friendship of fellow students.

Project work

Your five month research project gives you real research experience in Synthetic Biology. You will have the opportunity to work closely with a leading research team in the School and there are opportunities to work on industry led projects. You will have one-to-one supervision from an experienced member of the faculty, supported with supervision from associated senior researchers and industry partners as required.

The project can be carried out:
-With a research group at Newcastle University
-With an industrial sponsor
-With a research institute
-At your place of work

Accreditation

We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and 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.

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If you're looking for a career in the fight against cancer - this is the course for you. This full-time MRes offers two research projects to give your future career in cancer biology a boost. Read more

Research training at the computational/clinical translational science interface

If you're looking for a career in the fight against cancer - this is the course for you. This full-time MRes offers two research projects to give your future career in cancer biology a boost. With two streams on offer – Cancer Biology, and Cancer Informatics – we have the options available for you to choose the best way for you to use your life-sciences degree to meet your objective. We will provide you with a broad-training in research as well as theoretical and practical skills to help you take the next step in your career.

Streams

There are two streams available:

•Cancer Biology - http://www.imperial.ac.uk/medicine/study/postgraduate/masters-programmes/mres-cancer-biology/
•Cancer Informatics - http://www.imperial.ac.uk/medicine/study/postgraduate/masters-programmes/mres-cancer-biology-cancer-informatics/

Is this programme for you?

You will engage with both theoretical and practical elements. The theoretical elements will include why particular methods are used, assumptions they are based on and understanding the technical limitations and quality control of different data types. The practical elements will include data handling and the computational method employed for each data type.

When you enter your projects, you will perform novel bioinformatics-based research, accumulate experimental findings and exercise critical scientific thought in the interpretation of those findings. The research projects may also include a smaller component of wet-lab experiments to provide some validation of the findings from the bioinformatics research.

You will need to be an independent person, who is looking for a challenge. If you're not afraid of hard work, then we would welcome an application from you.

Application

Decisions on applications are made in batches, with the following deadlines for each batch:
•09:00 GMT (UTC) Tuesday, 31 January 2017
•09:00 BST (UTC+1) Wednesday, 26 April 2017
•09:00 BST (UTC+1) Monday, 31 July 2017

You will receive notification of a conditional offer or rejection in the weeks following these deadlines. If you do not hear from us, it is because you have been placed on the waiting list. We withhold the right to close application early, so ensure that you submit your application sooner, rather than later.

Please note that we are unable to consider your application without at least one academic reference from your most recent institution.

Programme structure

The course comprises an initial four/five week taught component in which the cellular and molecular basis of cancer biology are covered, plus an introduction to the clinical and pathological aspects of carcinogenesis. This information is contained within the lectures which will partly be on the lecturer's own research, making use of the excellent researchers we have within Imperial College London. Within this period will also be a series of workshops covering key transferable skills such as oral presentation of scientific data and grant writing. This is shared with the Cancer Biology stream.

While the Cancer Biology stream move into their first project, you will receive three weeks of specialist training in informatics which is comprised of lectures and workshops. You will then complete an initial assignment before beginning your first research placement of roughly 16 weeks, and then a second project of roughly 20 weeks. These will be within the recently created Imperial College Cancer Research UK Centre, the Faculty of Medicine at the Hammersmith Hospital campus of Imperial College, and other collaborating institutes across London (e.g. Institute of Clinical Sciences, The Francis Crick Institute).

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The two-year MSc Bioinformatics concerns a new scientific discipline with roots in computer science, statistics and molecular biology. Read more

MSc Bioinformatics

The two-year MSc Bioinformatics concerns a new scientific discipline with roots in computer science, statistics and molecular biology. Bioinformaticians apply information technology to store, retrieve and manipulate these data and employ statistical methods capable of analysing large amounts of biological data to predict gene functions and to demonstrate relationships between genes and proteins.

Programme summary

DNA contains information about life, but how is this information used? Biological data, such as DNA and RNA sequence information produced by next-generation sequencing techniques, is accumulating at an unprecedented rate. Life scientists increasingly use bioinformatics resources to address their specific research questions. Bioinformaticians bridge the gap between complex biological research questions and this complex data. Bioinformaticians use and develop computational tools to predict gene function(s) and to demonstrate and model relationships between genes, proteins and metabolites in biological systems. Bioinformatics is an interdisciplinary field that applies computational and statistical techniques to the classification, interpretation and integration of large-scale biological data sets. If different data types are joined then complex interactions in biological systems can be studied. The use of systems biology methods to study complex biological interactions offers a wealth of possibilities to understand various levels of aggregation and enables control of biological systems on different scales. Systems biology approaches are therefore quickly gaining importance in many disciplines of life sciences, such as in applied biotechnology where these methods are now used to develop strategies for improving production in fermentation. Other examples include bioconversion and enzymatic synthesis, and in the study of human metabolism and its alterations where systems biology methods are applied to understand a variety of complex human diseases, including metabolic syndromes and cancer. The Wageningen Master programme focuses on the practical application of bioinformatics and systems biology approaches in many areas of the Life Sciences. To ensure that students acquire a high level of understanding of modelling and computing principles, the students are trained in the fundamentals of database management, computer programming, structural and functional genomics, proteomics and systems biology methods. This training includes advanced elective courses in molecular biology and biostatistics.

Thesis tracks

Bioinformatics
The bioinformatics track focuses on the practical application of bioinformatics knowledge and skills in molecular life sciences. It aims at creating and using bioinformatics resources to address specific research questions. The knowledge and skills gained can be applied in many life science disciplines such as molecular & cell biology, biotechnology, (human) genetics, health & medicine and environmental & biobased technology.

Systems Biology
The systems biology track focuses on the study of the complex interactions in biological systems and on the emerging properties derived from these. Systems biology approaches to complex biological problems offer a wealth of possibilities to understand various levels of aggregation. It enables control of biological systems on completely different scales, ranging from the molecular cellular level to marine, plant, or animal ecosystems to a desired state. The knowledge and skills gained can be applied in many life science disciplines including molecular & cell biology, applied biotechnology, genetics, medicine and vaccine development, environmental and biobased technology.

Your future career

Bioinformatics and Systems Biology are new fast growing biology based interdisciplinary fields of research poorly served by the traditional curricula of Life Sciences. As demand has outpaced the supply of bioinformaticians, the first job after graduation is often a PhD project at a research institute or university. It is expected that five years after graduation, about one third will stay employed as a scientist at a university or research centre, while the others choose for careers at research-oriented pharmaceutical and biotechnological companies.

Alumnus Tom van den Bergh.
"It is sometimes difficult for doctors to diagnose genetic diseases caused by missense mutations. A missense mutation does not necessarily mean that you have the gene-associated disease and will become ill since not all missense mutations lead to appreciable protein changes." Tom created a database for Fabry’s disease for his final thesis. He wrote a computer programme that reads publications and stores all information about Fabry mutations in its database. Genetic researchers can, in turn, quickly access this database to determine if the mutation they found in a patient has already been addressed in literature and what the effects were.

Related programmes:
MSc Biotechnology
MSc Molecular Life Sciences
MSc Plant Biotechnology

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In recent years, biological research has become increasingly interdisciplinary, focusing heavily on mathematical modeling and on the analysis of system-wide quantitative information. Read more

Computational Life Science

In recent years, biological research has become increasingly interdisciplinary, focusing heavily on mathematical modeling and on the analysis of system-wide quantitative information. Sophisticated high-throughput techniques pose new challenges for data integration and data interpretation. The Computational Life Science (CompLife) MSc program at Jacobs University meets these challenges by covering computational, theoretical and mathematical approaches in biology and the life sciences. It is geared towards students of bioinformatics, computer science, physics, mathematics and related areas.

Program Features

The CompLife program is located at Jacobs University, a private and international English-language academic institution in Bremen, Germany. CompLife students at Jacobs University take a tailor-made curriculum comprising lectures, seminars and laboratory trainings. Courses cover foundational as well as advanced topics and methods. Core components of the program and areas of specialization include:

- Computational Systems Biology
- Computational Physics and Biophysics
- Bioinformatics
- RNA Biology
- Imaging and Modeling in Medicine
- Ecological Modeling
- Theoretical Biology
- Applied Mathematics
- Numerical Methods

For more details on the CompLife curriculum, please visit the program website at http://www.jacobs-university.de/complife.

Career Options

Graduates of the CompLife program are prepared for a career in biotechnology and biomedicine. Likewise, graduates of the program are qualified to move on to a PhD.

Application and Admission

The CompLife program starts in the first week of September every year. Please visit http://www.jacobs-university.de/graduate-admission or use the contact form to request details on how to apply. We are looking forward to receiving your inquiry.

Scholarships and Funding Options

All applicants are automatically considered for merit-based scholarships of up to € 12,000 per year. Depending on availability, additional scholarships sponsored by external partners are offered to highly gifted students. Moreover, each admitted candidate may request an individual financial package offer with attractive funding options. Please visit http://www.jacobs-university.de/study/graduate/fees-finances to learn more.

Campus Life and Accommodation

Jacobs University’s green and tree-shaded campus provides much more than buildings for teaching and research. It is home to an intercultural community which is unprecedented in Europe. A Student Activities Center, various sports facilities, a music studio, a student-run café/bar, concert venues and our Interfaith House ensure that you will always have something interesting to do.

For graduate students who would like to live on campus, Jacobs University offers accommodation in four residential colleges. Each college has its own dining room, recreational lounge, study areas, and common and group meeting rooms. Please visit http://www.jacobs-university.de/study/graduate/campus-life for more information.

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We offer an opportunity to train in one of the newest areas of biology. the application of engineering principles to the understanding and design of biological networks. Read more

Programme description

We offer an opportunity to train in one of the newest areas of biology: the application of engineering principles to the understanding and design of biological networks. This new approach promises solutions to some of today’s most pressing challenges in environmental protection, human health and energy production.

This MSc will provide you with a thorough knowledge of the primary design principles and biotechnology tools being developed in systems and synthetic biology, ranging from understanding genome-wide data to designing and synthesising BioBricks.

You will learn quantitative methods of modelling and data analysis to inform and design new hypotheses based on experimental data. The University’s new centre, SynthSys, is a hub for world-leading research in both systems and synthetic biology.

Programme structure

The programme consists of two semesters of taught courses followed by a research project and dissertation, which can be either modelling-based or laboratory-based.

Compulsory courses:

Applications of Synthetic Biology
Dissertation project
Information Processing in Biological Cells
Practical Systems Biology
Social Dimensions of Systems and Synthetic Biology
Tools for Synthetic Biology

Option courses:

Biobusiness
Biochemistry
Bioinformatics Algorithms
Bioinformatics Programming & System Management
Biological Physics
Computational Cognitive Neuroscience
Drug Discovery
Economics & Innovation in the Biotechnology Industry
Environmental Gene Mining & Metagenomics
Functional Genomic Technologies
Gene Expression & Microbial Regulation
Industry & Entrepreneurship in Biotechnology
Introduction to Scientific Programming
Molecular Phylogenetics
Neural Computation
Next Generation Genomics
Practical Skills in Biochemistry
Probabilistic Modelling and Reasoning
Statistics and Data Analysis
Stem Cells & Regenerative Medicine

Career opportunities

The programme is designed to give you a good basis for managerial or technical roles in the pharmaceutical and biotech industries. It will also prepare you for entry into a PhD programme.

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