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Masters Degrees (Computational Biology)

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The scheme is designed to introduce key, practice-based skills in statistics for Computational Biology. You will contribute knowledge to the design of Biological experiments to ensure that appropriate statistical analysis of experimental data is possible. Read more

About the course

The scheme is designed to introduce key, practice-based skills in statistics for Computational Biology. You will contribute knowledge to the design of Biological experiments to ensure that appropriate statistical analysis of experimental data is possible.

You will learn how to critically evaluate the application of specific statistical techniques to research problems in Computational Biology and then effectively interpret and report the results of analyses.

This master’s degree is all about computational biology and statistics and will be of interest to students that are looking for the minimum entry-level qualification for many excellent employment opportunities in pharmaceuticals, advanced agriculture and in public health.

The course is a collaboration between the departments of Computer Science, Maths and also the Institute of Biological Environmental and Rural Science. The study scheme will bring the departments together in research-led teaching in these areas and you will benefit from expertise and insight from these highly specialised departments. In the most recent Research Excellence Framework assessment (2014) it was found that 95% of the universities research was of an internationally recognised standard or higher.

Course structure and content

The duration of the course is twelve months full-time or 24 months part time. The academic year (September to September) is divided into three semesters: September to January; January to June; June to September. The course is available as a postgraduate certificate or diploma and can be taken part-time. Students must contact the department to discuss these options.

Core modules:

Frontiers in the Biosciences
Programming for Scientists
Research Skills and Personal Development for Scientists
Statistical Concepts, Methods and Tools
Machine Learning for Intelligent Systems
Research Skills and Personal Development for Scientists (1520)
Statistical Techniques for Computational Biology

Optional modules:

Dissertation

Contact Time

Approximately 10-14 hours a week in the first two semesters. During semester three you will arrange your level of contact time with your assigned supervisor.

Assessment

The programme comprises 180 credits. There are 120 credits of taught modules completed during Semester 1 and Semester 2. This is followed by a research dissertation (60 credits) in semester 3.

This degree will suit you:

- If you already have a background in one of biology, maths or computing and now want training in this exciting interdisciplinary area to enhance your current skills.

- If you have a high 2:2 degree or higher in a related discipline

- If you wish to gain academic expertise and practical experience in Computational Biology.

- If you wish to enter a career in Statistics for Computational Biology with opportunities to work in pharmaceuticals, advanced agriculture and public health.

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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

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 ANC 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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A minimum of 30 credits is required for the degree, excluding bridge courses. The graduate curriculum consists of seven core courses and additional elective courses, with an optional thesis (six credits) or research project (three credits). Read more

A minimum of 30 credits is required for the degree, excluding bridge courses. The graduate curriculum consists of seven core courses and additional elective courses, with an optional thesis (six credits) or research project (three credits).

Required Courses

  • Critical Thinking for the Life Sciences
  • Numerical Methods for Computation
  • Linear Algebra and Applications
  • Analytical Computational Neuroscience
  • Introduction to Biostatistics or Approaches to Quantitative Analysis in the Life Sciences
  • Computational Ecology
  • Foundations of Bioinformatics
  • Master's Project or Masters Thesis

Electives

Select two of the following:

  • Foundations of Mathematical Biology
  • Regression Analysis Methods
  • Design and Analysis of Experiments
  • Advanced Physical Chemistry
  • Cell Biology: Methods & Appl
  • Cell Surface Recept
  • Computational Biology
  • Systems Neuroscience
  • Systems Computational Neuroscience
  • Comparative Animal Physiology
  • Intermediate Differential Equations
  • Biomathematics I: Biological Waves and Oscillations


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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/1237/computational-biology

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 houses a dynamic research community with five major research themes:

  • industrial biotechnology
  • infection and drug resistance
  • cancer and age-related diseases
  • cellular architecture and dynamics
  • reproduction, evolution and genomics

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 - https://www.kent.ac.uk/courses/postgraduate/how-to-apply/



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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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Goal of the pro­gramme. Ecology and evolutionary biology offer a perspective on biology from the level of genes to communities of species. Read more

Goal of the pro­gramme

Ecology and evolutionary biology offer a perspective on biology from the level of genes to communities of species.

In the master's degree program, you can become familiar with a wide variety of topics in three areas: ecology, evolutionary biology and conservation biology. You can choose studies from any of these areas, as well as from other master's degree programmes. The programme is diverse and multidisciplinary: teaching is done with lectures, laboratory and computer training courses, interactive seminars, study tours and field courses. The field courses range from the northern subarctic region to tropical rainforests.

Our wide expertise extends from molecular ecology to population and community biology. The Centres of Excellence of Metapopulation Biology and Biological Interactions are located in our department.

Our programme offers you a wide range of options: evolutionary biology or genetics for those interested in ecological genetics and genomics, as well as the ability to take advantage of the high-quality molecular ecology and systematics laboratory; conservation biology for those interested in regional or global environmental problems; and ecological modelling skills for those interested in computational biology. Our training also offers Behavioural Ecology. 

Ecology, evolutionary biology and conservation biology are not only fascinating topics for basic research, they also have a key role in addressing global environmental challenges.

Upon graduating from the Master's degree in ecology and evolutionary biology programme, you will:

  • Have mastered the main theories and methods in ecology and evolutionary biology and be able to apply them to practical problems
  • Be able to plan and carry out a scientific research project
  • Have read the relevant scientific literature and be able to utilise your expertise in different types of work
  • Be able to work as an expert in your field
  • Be able to to write good scientific English
  • Be able to work in research projects and groups
  • Be able to continue on to doctoral studies

Further information about the studies on the Master's programme website.

Pro­gramme con­tents

The Master's degree program includes studies of ecology, evolutionary biology and conservation biology. The studies are organised in modules. You can affect the content of the studies by planning your personal curriculum. You can study the following themes:

  • Ecology studies the abundance and distribution of species (animals, plants, microbes) and the interactions among them and with the environment. The perspective ranges from the molecular to the ecosystem level. In ecology, a central question is: Why are some species able to invade new habitats and displace native species? Which species are able to adapt to environmental change or migrate with the changing climate, and which species will become extinct?
  • Evolutionary biology examines the processes which support biodiversity on its various levels (genes – individuals – populations – species – ecosystems). You will learn about the theory of evolution and how to use population genetics and genomics methods in researching evolutionary issues.
  • Conservation Biology studies the depletion of biodiversity, its causes and consequences. You will learn to apply ecological theory to the problems of environmental conservation, to assess the effectiveness of methods of conservation, as well as to resolve the problems relating to conservation e.g. by modelling and computational methods. The training emphasizes the importance of interdisciplinary education in the area of conservation.


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There is currently a worldwide shortage in graduates qualified in Bioinformatics and the skills to interpret the data that is going to underpin advances in biology and medicine in 21st Century. Read more

There is currently a worldwide shortage in graduates qualified in Bioinformatics and the skills to interpret the data that is going to underpin advances in biology and medicine in 21st Century. With the advent of Personalised Medicine, the demand for specialists in Computational Biology and Bioinformatics will further increase. This gives you the opportunity to build your transferable skill set across a range of cutting edge technologies and start building a career in this central facet of modern biology.

Students completing the MSc course in Bioinformatics and Computational Genomics will have the necessary skills and knowledge to undertake research and development in industry (Biotechnology, Pharmaceutical, Diagnostic companies), in medical research centres and in academic institutions worldwide.

Computational, statistical and machine learning methods form an integral part of modern research in Molecular Biology, Cell Biology, Pharmacology, Public Health Care and in Medicine. The past decade has seen enormous progress in the development of molecular and biomedical technologies. Today’s high-throughput array and sequencing techniques produce data in the range of terabytes on a daily basis and new technologies continuously emerge. This will further increase the stream of data available for biomedical research. For this reason analyzing, visualizing and managing this huge amount of data is a challenging task. The Queen’s MSc course in Bioinformatics and Computational Genomics targets these data-driven challenges of modern science. The course is open to graduates in computer science, life sciences, physics or statistics.

The programme will consist of an Introductory short course (two weeks) in Cell Biology, followed by modules in:

• Genomics & Genetics

• Analysis of Gene Expression

• Scientific Programming & Statistical Computing

• Algorithmic Biology

• Statistical Biology

• Bioimaging Informatics

• Research project : MSc dissertation



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This MRes Advanced Biological Sciences lets you take your enthusiasm deeper with a research project carried out over a full calendar year supported by 4 modules that further develop your skills and knowledge. Read more

This MRes Advanced Biological Sciences lets you take your enthusiasm deeper with a research project carried out over a full calendar year supported by 4 modules that further develop your skills and knowledge.

The Institute of Integrative Biology

The Institute of Integrative Biology lies at the heart of a thriving science campus in Liverpool city centre. Based primarily in the Biosciences Building with additional sites at Leahurst Veterinary Field Station and Ness Botanic Gardens, we provide one of the most diverse, vibrant and integrated biosciences environments in the UK. The Institute comprises 220 staff (including 75 Principal Investigators) and 150 postgraduate students.

We have well established world-class research facilities that support scientists across all four of the Institute's research themes:

  • Dynamics and management of host-microbe interactions
  • Molecular basis of therapeutic targeting
  • From genes to biological systems
  • Adaptation to environmental change

Research in the Institute spans the complete range of biological scales from genes and genetic regulation through proteins, post-translational modification and cellular function to whole organisms, populations and ecosystems. We use state-of-the-art “omics” technologies to generate large data-sets both within and across these scales. We also develop new mathematical and computational models to make sure we can fully exploit these data.

The facilities include the Centre for Genomic Research, the GeneMill Synthetic Biology Laboratory, the Centre for Proteome Research, the Computational Biology Facility, the Centre for Cell Imaging, the NMR Centre for Structural Biology, the Barkla X-laboratory of Biophysics and the Henry Wellcome Laboratory of Mammalian Behaviour and Evolution. There are also excellent cell, microbial and plant culture facilities.

Through our research partnerships with companies such as Unilever, strong global links into major research organisations in Europe, Japan, Brazil, USA and China and our scientific outreach to schools and the community, we are having true impact across the world. Our postgraduate students enjoy a first class experience with strong supervision and mentorship in an exciting research environment. Our Athena SWAN Gold award is evidence of our full commitment to providing opportunities for development to all, regardless of background or gender. 

What is in the MRes Advanced Biological Sciences ?

This Master of Research programme is designed for those who want to move on to a research career. The programme consists of a 120 credit research project, during which you will work alongside PhD students and full-time researchers as a member of one of our research groups.

This is supported by four 15 credit taught M-level modules. At least two of these will deepen your scientific knowledge relevant to your research project. They will be selected from advanced taught modules in areas of animal behaviour, cancer biology, medical genetics, environmental biology, food security, microbiology, bioinformatics or biochemistry. There is one compulsory module in research methods and their applications within the life sciences and a second compulsory module is taken from a selection that include statistics, programming for life sciences, professional & employability skills or bespoke skills development.

The result is many pathways to MRes awards, affording applicants the opportunity to develop their own postgraduate degree programmes.

The taught modules take place in the autumn and spring semesters, alongside your initial work on your research project. In the summer semester you concentrate on your research.

The degree programme can therefore be based around your particular areas of interest. The title of your degree award will reflect your pathway of choice.

Example pathways

Advanced Biological Sciences (Animal Sciences)

Advanced Biological Sciences (Bioinformatics)

Advanced Biological Sciences (Biotechnology)

Advanced Biological Sciences (Cell Signalling)

Advanced Biological Sciences (Chemical Biology)

Advanced Biological Sciences (Conservation Biology)

Advanced Biological Sciences (Evolution and Behavioural Biology)

Advanced Biological Sciences (Food Security)

Advanced Biological Sciences (Functional and Comparative Genomics)

Advanced Biological Sciences (Host: Parasite Biology)

Advanced Biological Sciences (Microbiology)

Advanced Biological Sciences (Molecular Oncology)

Advanced Biological Sciences (Plant Sciences)

Advanced Biological Sciences (Structural Biology)

Advanced Biological Sciences (Post-Genomic Sciences)

The taught modules ensure that you develop the academic background and skills to excel in research.

Non-native English speakers are offered support in communication skills. This is taught by members of The University's English Language Unit and is designed to improve your English in a scientific context.

From molecules to humans, individuals to ecosystems, our research programmes – and scientists – are making a difference. Join us on the journey.



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Overview. The MSc Mathematical Medicine and Biology will provide you with skills suitable for a research career in the exciting and growing field of mathematical medicine and biology. Read more

Overview

The MSc Mathematical Medicine and Biology will provide you with skills suitable for a research career in the exciting and growing field of mathematical medicine and biology.

You will take core modules in biology and the application of mathematics to medicine and biology. More advanced modules will introduce research topics in biomedical mathematics, including options in Computational Biology and Theoretical Neuroscience.

The taught training programme will be followed by a substantial individual project leading to a dissertation.

Throughout the course, the exceptional strength of the Centre for Mathematical Medicine and Biology will facilitate your hands-on experience of interdisciplinary biomedical research.

Some teaching activities will take place at the Sutton Bonington campus. The University provides a regular hopper bus between University Park and Sutton Bonington.

Key facts:

- This course is informed by the work being carried out in the Centre for Mathematical Medicine and Biology.

- 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 eighth 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).

Module details

Biomolecular Data and Networks

Cell Structure and Function for Engineers

Computational and Systems Biology

Mathematical Medicine and Biology

Mathematical Medicine and Biology Dissertation

Practical Biomedical Modelling

Theoretical Neuroscience

Topics in Biomedical Mathematics

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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Graduate education in Computational Science and Engineering (CMSE) at Koç University is offered through an interdisciplinary program among the Departments of the College of Arts and Sciences and the College of Engineering. Read more
Graduate education in Computational Science and Engineering (CMSE) at Koç University is offered through an interdisciplinary program among the Departments of the College of Arts and Sciences and the College of Engineering. In this program graduate students are trained on modern computational science techniques and their applications to solve scientific and engineering problems. New technological problems and associated research challenges heavily depend on computational modeling and problem solving. Because of the availability of powerful and inexpensive computers model-based computational experimentation is now a standard approach to analysis and design of complex systems where real experiments can be expensive or infeasible. Graduates of the CMSE Program should be capable of formulating solutions to computational problems through the use of multidisciplinary knowledge gained from a combination of classroom and laboratory experiences in basic sciences and engineering. Individuals with B.S. degrees in biology, chemistry, physics, and related engineering disciplines should apply for graduate study in the CMSE Program.

Current faculty projects and research interests:

• Computational Biology & Bioinformatics
• Computational Chemistry
• Computational Physics
• Molecular Dynamics and Simulation
• Parallel and High Performance Computing
• Computational Fluid Dynamics
• Dynamical and Stochastic Systems
• Quantum Mechanics of Many Body Systems
• Electronic Design Automation
• Numerical Methods
• Simulation of Material Synthesis
• Structural Dynamics
• Biomedical Modeling and Simulation
• Virtual Environments

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STUDY MOLECULES TO SOLVE BIG ISSUES. Read more

STUDY MOLECULES TO SOLVE BIG ISSUES

The Master in Molecular and Cellular Life Sciences (MCLS) is research oriented and takes a multidisciplinary approach to study related to health and disease in cells and organisms. By the end of the programme you will gain sufficient fundamental knowledge to start working on applications in the field of medical and biotechnological issues. These applications may include the development of new medicines and vaccines, new strategies for crop improvement, or the development of enzymes to be used in industry. 

THE RIGHT CHOICE FOR YOU?

MCLS is the ideal Master’s programme if you are interested in molecules as the basis of life and disease and if you want to know how chemistry, biology, biomedical sciences, and physics contribute to our understanding of how these molecules work. The interplay of molecules in cells and organisms is the central focus of the programme. 

The Dutch Master's Selection Guide (Keuzegids Masters 2017) ranked this programme as the best in the field of Chemistry in the Netherlands.

PROGRAMME OBJECTIVE 

You will develop extensive knowledge about cellular processes such as cellular signaling, membrane biogenesis and intracellular transport. You will also learn skills and methods to study the molecules involved in these processes by using biochemistry, structural biology, cell biology, biophysics, computational biology, proteomics and genomics. The programme offers you the flexibility to choose any specialisation within the field of molecular and cellular life sciences.

Tracks

Within this Master’s programme you can choose one of four tracks:



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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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