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Masters Degrees (Computational Ecology)

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Our Computational Ecology MSc gives you knowledge and skills to work with ecological ‘big data’. It focuses on mathematical and statistical theory necessary for data interpretation and analysis. Read more

Our Computational Ecology MSc gives you knowledge and skills to work with ecological ‘big data’. It focuses on mathematical and statistical theory necessary for data interpretation and analysis.

About this course

You will be suitable for the course if you are:

  • an ecologist involved in scientific research
  • a graduate in mathematics or computing.

WHAT YOU''LL LEARN:

Our course was created to close the knowledge gap in ecological research. It provides a sound grounding in important components of any research project, including:

  • mathematics
  • statistics
  • computer programming
  • genetics
  • ‘big data’ analysis and interpretation

We will teach you how to handle a range of data eg:

  • GPS tracking of wildlife
  • remote-sensed landscape data
  • bioinformatics

After successfully completing the course you will have the skills to undertake research projects in academia or industry.



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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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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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This MRes is designed for students with a passion for the diversity of life on earth, who are looking to further their knowledge and experience of quantitative techniques in ecology, evolution and conservation. Read more

This MRes is designed for students with a passion for the diversity of life on earth, who are looking to further their knowledge and experience of quantitative techniques in ecology, evolution and conservation.

The course is focused on current topics in modern computational and quantitative biology such as the interactions between ecological and evolutionary dynamics, the effects of climate change on biological systems, and complex ecological and evolutionary networks.

You gain postgraduate-level training in research skills during the intensive one-year full-time programme.

Careers

You graduate with a range of transferrable professional skills that help to give a major edge in competing for PhDs and jobs. Your experience of conducting research projects will allow you to make a more informed decision on the area of research and specific PhD project you may wish to undertake in the future.

This course is the ideal training for students looking to pursue a career in academic, government or non-governmental organisations engaged in research into biodiversity.

Further information

For full information on this course, including how to apply, see: http://www.imperial.ac.uk/study/pg/life-sciences/computational-methods-ecology-evolution-mres/

If you have any enquiries you can contact our team at:



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In this unique course we teach quantitative methods and biological concepts together, through application of the methods to cutting-edge biological research problems. Read more

In this unique course we teach quantitative methods and biological concepts together, through application of the methods to cutting-edge biological research problems.

The focus is on current topics in modern quantitative biology, such as interactions between ecological and evolutionary dynamics, and the effects of climate change on ecological communities.

You will also have the chance to develop your knowledge in mathematical, statistical, and computing tools through their application to important research problems.

Over the past 10–20 years, biology has become increasingly quantitative, and mathematical sciences have in turn been increasingly influenced by biology.

It has been said that “mathematics is biology's next microscope, only better” (Cohen, Plos Biology, 2004) because mathematical, statistical, and computational sciences will continue to reveal unsuspected and entirely new worlds within biology, just as the microscope revealed previously unseen worlds following its invention.

It has also been said that “biology is mathematics' next physics, only better” (Cohen, Plos Biology) because biology will in turn continue to spur major new developments in computation, mathematics and statistics, just as physics has done in past centuries.

This course is suitable for:

  • Life scientists wishing to expand their quantitative skills in light of the increasingly quantitative nature of modern biology
  • Physical scientists (mathematicians, physicists, statisticians, computer scientists) with a strong interest in biology

Careers

The course serves as ideal preparation for either PhD studies or employment in fields of applied quantitative biology, such as resource management and conservation.

Further information

For full information on this course, including how to apply, see: http://www.imperial.ac.uk/study/pg/life-sciences/computational-methods-ecology-evolution/

If you have any enquiries you can contact our team at:



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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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Goal of the pro­gramme. Life Sciences.  is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (. Read more

Goal of the pro­gramme

Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE).

The Master's Programme is offered by the Faculty of Science. Teaching is offered in co-operation with the Faculty of Medicine and the Faculty of Biological and Environmental Sciences. As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The LSI programme is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics. As a graduate of the LSI programme you will:

  • Have first class knowledge and capabilities for a career in life science research and in expert duties in the public and private sectors
  • Competence to work as a member of a group of experts
  • Have understanding of the regulatory and ethical aspects of scientific research
  • Have excellent communication and interpersonal skills for employment in an international and interdisciplinary professional setting
  • Understand the general principles of mathematical modelling, computational, probabilistic and statistical analysis of biological data, and be an expert in one specific specialisation area of the LSI programme
  • Understand the logical reasoning behind experimental sciences and be able to critically assess research-based information
  • Have mastered scientific research, making systematic use of investigation or experimentation to discover new knowledge
  • Have the ability to report results in a clear and understandable manner for different target groups
  • Have good opportunities to continue your studies for a doctoral degree

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

Pro­gramme con­tents

The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.

Algorithmic bioinformatics with the Genome-scale algorithmicsCombinatorial Pattern Matching, and Practical Algorithms and Data Structures on Strings research groups. This specialisation area educates you to be an algorithm expert who can turn biological questions into appropriate challenges for computational data analysis. In addition to the tailored algorithm studies for analysing molecular biology measurement data, the curriculum includes general algorithm and machine learning studies offered by the Master's Programmes in Computer Science and Data Science.

Applied bioinformaticsjointly with The Institute of Biotechnology and genetics.Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.

Biomathematics with the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group. 

Biostatistics and bioinformatics is offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational GeneticsComputational Genomics and Computational Systems Medicine in FIMM. Topics and themes include statistical, especially Bayesian methodologies for the life sciences, with research focusing on modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of collaborative topics in various biomedical disciplines. In particular, research and teaching address questions of population genetics, phylogenetic inference, genome-wide association studies and epidemiology of complex diseases.  

Eco-evolutionary Informatics with ecology and evolutionary biology, in which several researchers and teachers have a background in mathematics, statistics and computer science. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Evolutionary biology studies processes supporting biodiversity on different levels from genes to populations and ecosystems. These sciences have a key role in responding to global environmental challenges. Mathematical and statistical modelling, computer science and bioinformatics have an important role in research and teaching.

Systems biology and medicine with the Genome-scale Biology Research Program in BiomedicumThe focus is to understand and find effective means to overcome drug resistance in cancers. The approach is to use systems biology, i.e., integration of large and complex molecular and clinical data (big data) from cancer patients with computational methods and wet lab experiments, to identify efficient patient-specific therapeutic targets. Particular interest is focused on developing and applying machine learning based methods that enable integration of various types of molecular data (DNA, RNA, proteomics, etc.) to clinical information.



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Today more than ever, quantitative skills form an essential basis for successful careers in ecology, conservation, and animal and human health. Read more

Today more than ever, quantitative skills form an essential basis for successful careers in ecology, conservation, and animal and human health. This Masters programme provides specific training in data collection, modelling and statistical analyses as well as generic research skills. It is offered by the Institute of Biodiversity, Animal Health and Comparative Medicine (IBAHCM), a grouping of top researchers who focus on combining field data with computational and genetic approaches to solve applied problems in epidemiology and conservation.

Why this programme

  • This programme encompasses key skills in monitoring and assessing biodiversity critical for understanding the impacts of environmental change.
  • It covers quantitative analyses of ecological and epidemiological data critical for animal health and conservation.
  • You will have the opportunity to base your independent research projects at the university field station on Loch Lomond (for freshwater or terrestrial-based projects); Millport field station on the Isle of Cumbrae (for marine projects); or Cochno Farm and Research Centre in Glasgow (for research based on farm animals). We will also assist you to gain research project placements in zoos or environmental consulting firms whenever possible.
  • The uniqueness of the programme is the opportunity to gain core skills and knowledge across a wide range of subjects, which will enhance future career opportunities, including entrance into competitive PhD programmes. For example, there are identification based programmes offered elsewhere, but most others do not combine practical field skills with molecular techniques, advanced informatics for assessing biodiversity based on molecular markers, as well as advanced statistics and modelling. Other courses in epidemiology are rarely ecologically focused; the specialty in IBAHCM is understanding disease ecology, in the context of both animal conservation and implications for human public health.
  • You will be taught by research-active staff using the latest approaches in quantitative methods, sequence analysis, and practical approaches to assessing biodiversity, and you will have opportunities to actively participate in internationally recognised research. Some examples of recent publications lead by students in the programme:
  • Blackburn, S., Hopcraft, J. G. C., Ogutu, J. O., Matthiopoulos, J. and Frank, L. (2016), Human-wildlife conflict, benefit sharing and the survival of lions in pastoralist community-based conservancies. J Appl Ecol. doi:10.1111/1365-2664.12632. 
  • Rysava, K., McGill, R. A. R., Matthiopoulos, J., and Hopcraft, J. G. C. (2016) Re-constructing nutritional history of Serengeti wildebeest from stable isotopes in tail hair: seasonal starvation patterns in an obligate grazer. Rapid Commun. Mass Spectrom., 30:1461-1468. doi: 10.1002/rcm.7572.
  • Ferguson, E.A., Hampson, K., Cleaveland, S., Consunji, R., Deray, R., Friar, J., Haydon, D. T., Jimenez, J., Pancipane, M. and Townsend, S.E., 2015. Heterogeneity in the spread and control of infectious disease; consequences for the elimination of canine rabies. Scientific Reports, 5, p. 18232. doi: 10.1038/srep18232.
  • A unique strength of the University of Glasgow for many years has been the strong ties between veterinarians and ecologists, which has now been formalised in the formation of the IBAHCM. This direct linking is rare but offers unique opportunities to provide training that spans both fundamental and applied research.

Programme structure

The programme provides a strong grounding in scientific writing and communication, statistical analysis, and experimental design. It is designed for flexibility, to enable you to customise a portfolio of courses suited to your particular interests.

You can choose from a range of specialised options that encompass key skills in

  • monitoring and assessing biodiversity – critical for understanding the impacts of environmental change
  • quantitative analyses of ecological and epidemiological data – critical for animal health and conservation
  • ethics and legislative policy – critical for promoting humane treatment of both captive and wild animals.

A total of 180 credits are required, with 50 flexible credits in the second term. See the accompanying detailed course descriptions found in the IBAHCM Masters Programme Overview. When selecting options, please email the relevant course coordinator as well as registering using MyCampus.

Term 1: Core courses (assessment in %)

  • Key research skills (scientific writing, introduction to R, introduction to linear models; advanced linear models, experimental design). Coursework – 60%; scientific report – 40%
  • Spatial Ecology and Biodiversity. Coursework – 60%; assignment – 40%

Term 2: Core courses

  • Programming in R. Coursework – 50%; assignment – 50%

Term 2: Optional courses

  • Biodiversity Informatics. Coursework – 25%; assignment – 75%
  • GIS for Ecologists. Set exercise – 60%; critical review – 40%
  • Infectious Disease Ecology & the Dynamics of Emerging Disease. Coursework – 50%; assignment – 50%
  • Introduction to Bayesian Statistics. Coursework – 50% assignment – 50%
  • Invertebrate Identification. Coursework – 20%; class test – 40%; assignment – 40%
  • Molecular Analyses for Biodiversity and Conservation. Coursework – 40%; assignment – 60%
  • Molecular Epidemiology & Phylodynamics. Coursework – 40%; assignment – 60%
  • Multi-species Models. Coursework – 50%; assignment – 50%
  • Single-species Population Models. Coursework – 30%; assignment – 70%
  • Vertebrate Identification. Coursework – 20%; class test – 40%; assignment – 40%
  • Human Dimensions of Conservation*. Press statement – 50%; assignment – 50%
  • Principles of Conservation Ecology*. Coursework – 30%; set exercise – 15%; poster – 55%
  • Protected Area Management*. Coursework – 50%; assignment – 50%
  • Animal Ethics. Oral presentation – 50%; reflective essay – 50%
  • Biology of Suffering. Essay – 100%
  • Care of Captive Animals. Report – 100%
  • Enrichment of Animals in Captive Environments. Essay – 100%
  • Legislation & Societal Issues. Position paper – 50%; press release – 50%
  • Welfare Assessment. Critical essay – 100%

Term 3: Core MSc Component

  • Research project. Research proposal – 25%; project report – 60%; supervisor’s assessment –15%

Career prospects

You will gain core skills and knowledge across a wide range of subjects that will enhance your selection chances for competitive PhD programmes. In addition to academic options, career opportunities include roles in zoos, environmental consultancies, government agencies, ecotourism and conservation biology, and veterinary or public health epidemiology.



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Ecologists and evolutionary biologists now routinely use next-generation DNA sequencing in their research, and graduates who are skilled in both genome analysis as well as ecology and evolution are rare. Read more

Ecologists and evolutionary biologists now routinely use next-generation DNA sequencing in their research, and graduates who are skilled in both genome analysis as well as ecology and evolution are rare. Genome-enabled approaches are helping rapidly to advance our understanding of the dynamic relationship between genotype, phenotype and the environment.

Our programme will give you cross-disciplinary skills in a rare combination of areas of expertise, from bioinformatics and evolutionary inference to computational biology and fieldwork.

You will be taught by researchers who apply genomic methods to a wide range of issues in ecology and evolution, from bat food-webs and genome evolution to microbial biodiversity in natural and engineered ecosystems. For example, Professor Steve Rossiter carries out world-leading research on bat genome evolution; Dr Yannick Wurm has discovered a social chromosome in fire-ants; and Dr China Hanson is using genetic methods to study microbial biogeography. This means that teaching on our programme is informed by the latest developments in this field, and your individual research project can be at the forefront of current scientific discovery. 

You will conduct your own substantive six-month research project, which may be jointly supervised by contacts from related institutes or within industry. You will also take part in a field course in Borneo - see photos from a recent trip on Flickr - giving you the opportunity to develop first hand experience of theory in action.

Programme highlights

  • Work with leading researchers in environmental genomics - learn more on the Evolution and Genetics research group page 
  • Two-week tropical ecology field trip (currently to Borneo)
  • Strong foundation for careers in consultancy, environmental policy and management or research
  • Strong foundation for PhD training in any area of genomics, ecology or evolution

Research and teaching

By choosing to study at a Russell Group university you will have access to excellent teaching and top class research. You can find out more about our research interests and view recent publications on the School of Biological and Chemical Science's Evolution and Genetics group page.

Structure

This MSc programme combines taught modules with individual and collaborative research projects. You will apply the knowledge and techniques from your taught modules in a practical setting and may be able to publish your project findings.

If you have any questions about the content or structure, contact the programme director Dr Christophe Eizaguirre.

Taught modules

  • Genome Bioinformatics: Covers the essential aspects of next generation sequence (NGS) analysis, including genome assembly, variant calling and transcriptomics. Also covers essential computer skills needed for bioinformatics, such as Linux and using our high performance computing cluster.
  • Coding for scientists: Assuming no prior programming knowledge, teaches you how to program in Python, using biological examples throughout. Python is one of the most popular languages in the bioinformatics community, and understanding Python provides the perfect foundation for learning other languages such as Perl, Ruby and Java.
  • Statistics and bioinformatics: Covers core statistics methods, within the R statistical computing environment. R has become the de facto environment for downstream data analysis and visualisation in biology, thanks to the hundreds of freely available R packages that allow biological data analysis solutions to be created quickly and reliably.
  • Post-genomics bioinformatics: Introduces techniques that have developed as a consequence of developments in genomics (i.e. transcriptomics, proteomics, metabolomics, structural biology and systems biology) with particular emphasis on the data analysis aspects. Practicals cover the popular Galaxy framework, advanced R, and machine learning.
  • Research frontiers in evolutionary biology: Exploring the frontiers of research in evolutionary biology. Topics covered will include: incongruence in phylogenetic trees, neutral versus selective forces in evolution, the origin of angiosperms, the origin of new genes, the evolution of sociality, the significance of whole genome duplication and hybridisation. Current methods being used to tackle these areas will be taught, with an emphasis on DNA sequence analysis and bioinformatics.

Research modules

  • Evolutionary/Ecological Analysis/Software Group Project module: Students are organised into small teams (3-4 members per team). Each team is given the same genomic or transcriptomic data set that must be analysed by the end of the module. Each team must design an appropriate analysis pipeline, with specific tasks assigned to individual team members. This module serves as a simulation of a real data analysis environment, providing invaluable experience for future employability.
  • Individual Research Project (50 per cent of the programme)


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

We offer MPhil supervision in the following research areas:

Motor systems development, plasticity and function

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

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

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

Auditory neuroscience

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

Pain

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

Psychobiology

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

Neurotoxicology

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

Forensic psychiatry and clinical psychology

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

Systems and computational neuroscience

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

Behaviour and evolution

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

Visual perception and human cognition

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

Pharmacy

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

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This MSc provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions. Read more

This MSc provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions.

About this degree

Students develop an understanding of the processes undertaken to arrive at a suitable mathematical model and are taught the fundamental analytical techniques and computational methods used to develop insight into system behaviour. The programme introduces a range of problems - industrial, biological and environmental - and associated conceptual models and solutions.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits), and a research dissertation (60 credits). 

The part-time option normally spans two years. The eight taught modules are spread over the two years. The research dissertation is taken in the summer of the second year.

Core modules

  • Advanced Modelling Mathematical Techniques
  • Nonlinear Systems
  • Operational Research
  • Computational and Simulation Methods
  • Frontiers in Mathematical Modelling and its Applications

Optional modules

  • Asymptotic Methods & Boundary Layer Theory
  • Biomathematics
  • Cosmology
  • Evolutionary Game Theory and Population Genetics
  • Geophysical Fluid Dynamics
  • Mathematical Ecology
  • Quantitative and Computational Finance
  • Theory of Traffic Flow
  • Waves and Wave Scattering

Dissertation/report

All MSc students undertake an independent research project, which culminates in a dissertation of approximately 15,000-words and a project presentation.

Teaching and learning

The programme is delivered through seminar-style lectures and problem and computer-based classes. Student performance is assessed through a combination of unseen examination and coursework. For the majority of courses, the examination makes up between 90–100% of the assessment. The project is assessed through the dissertation and an oral presentation.

Further information on modules and degree structure is available on the department website: Mathematical Modelling MSc

Careers

Our graduates have found employment in a wide variety of organisations such as Hillier-Parker, IBM, Swissbank, Commerzbank Global Equities, British Gas, Harrow Public School, Building Research Establishment and the European Centre for Medium-Range Weather-Forecasting. 

Recent career destinations for this degree

  • Actuarial Analyst, KPMG
  • Data Scientist, Echobox
  • Graduate Technical Professional, AVEVA
  • PhD in Biochemical Engineering, UCL
  • Engineer, Erds (EDF)

Employability

Finance, actuarial and accountancy professionals are constantly in demand for their high-level mathematical skills and recent graduates have taken positions in leading finance-related companies such as UBS, Royal Bank of Scotland, Societe Generale, PricewaterhouseCoopers, Deloitte, and KPMG.

In the engineering sector, one recent graduate has progressed to a mathematical modelling role at a leading transportation planning consultancy; another became a graduate trainee at a business segment of Schlumberger that provides reservoir imaging, monitoring, and development services.

In addition, a number of graduates have remained in education either progressing to a PhD or entering the teaching profession.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

UCL Mathematics is internationally renowned for its excellent individual and group research that involves applying modelling techniques to problems in industrial, biological and environmental areas.

The department hosts a stream of distinguished international visitors. In recent years four staff members have been elected fellows of the Royal Society, and the department publishes the highly regarded research journal Mathematika.

This MSc enables students to consolidate their mathematical knowledge and formulate basic concepts of modelling before moving on to case studies in which models have been developed for issues motivated by industrial, biological or environmental considerations.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Mathematics

82% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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Anthropology prides itself on its inclusive and interdisciplinary focus. It takes a holistic approach to human society, combining biological and social perspectives. Read more
Anthropology prides itself on its inclusive and interdisciplinary focus. It takes a holistic approach to human society, combining biological and social perspectives.

All of our Anthropology Master’s programmes are recognised by the Economic and Social Research Council (ESRC) as having research training status, so successful completion of these courses is sufficient preparation for research in the various fields of social anthropology. Many of our students go on to do PhD research. Others use their Master’s qualification in employment ranging from research in government departments to teaching to consultancy work overseas.

We welcome students with the appropriate background for research. If you wish to study for a single year, you can do the MA or MSc by research, a 12-month independent research project.

If you are interested in registering for a research degree, you should contact the member of staff whose research is the most relevant to your interests. You should include a curriculum vitae, a short (1,000-word) research proposal, and a list of potential funding sources.

About the School of Anthropology and Conservation

Kent has pioneered the social anthropological study of Europe, Latin America, Melanesia, and Central and Southeast Asia, the use of computers in anthropological research, and environmental anthropology in its widest sense (including ethnobiology and ethnobotany).

Our regional expertise covers Europe, the Middle East, Central, Southeast and Southern Asia, Central and South America, Amazonia, Papua New Guinea, East Timor and Polynesia. Specialisation in biological anthropology includes forensics and paleopathology, osteology, evolutionary psychology and the evolutionary ecology and behaviour of great apes.

Course structure

The first year may include coursework, especially methods modules for students who need this additional training. You will work closely with one supervisor throughout your research, although you have a committee of three (including your primary supervisor) overseeing your progress. If you want to research in the area of applied computing in social anthropology, you would also have a supervisor based in the School of Computing.

Research areas

- Social Anthropology

The related themes of ethnicity, nationalism, identity, conflict, and the economics crisis form a major focus of our current work in the Middle East, the Balkans, South Asia, Amazonia and Central America, Europe (including the United Kingdom), Oceania and South-East Asia.

Our research extends to inter-communal violence, mental health, diasporas, pilgrimage, intercommunal trade, urban ethnogenesis, indigenous representation and the study of contemporary religions and their global connections.

We research issues in fieldwork and methodology more generally, with a strong and expanding interest in the field of visual anthropology. Our work on identity and locality links with growing strengths in customary law, kinship and parenthood. This is complemented by work on the language of relatedness, child health and on the cognitive bases of kinship terminologies.

A final strand of our research focuses on policy and advocacy issues and examines the connections between morality and law, legitimacy and corruption, public health policy and local healing strategies, legal pluralism and property rights, and the regulation of marine resources.

- Environmental Anthropology and Ethnobiology

Work in these areas is focused on the Centre for Biocultural Diversity. We conduct research on ethnobiological knowledge systems and other systems of environmental knowledge as well as local responses to deforestation, climate change, natural resource management, medical ethnobotany, the impacts of mobility and displacement and the interface between conservation and development. Current projects include trade in materia medica in Ladakh and Bolivia, food systems, ethno-ornithology, the development of buffer zones for protected areas and phytopharmacy among migrant diasporas.

- Digital Anthropology: Cultural Informatics, Social Invention and Computational Methods

Since 1985, we have been exploring and applying new approaches to research problems in anthropology – often, as in the case of hypermedia, electronic and internet publishing, digital media, expert systems and large-scale textual and historical databases, up to a decade before other anthropologists. Today, we are exploring cloud media, semantic networks, multi-agent modelling, dual/blended realities, data mining, smart environments and how these are mediated by people into new possibilities and capabilities.

Our major developments have included advances in kinship theory and analysis supported by new computational methods within field-based studies and as applied to detailed historical records; qualitative analysis of textual and ethnographic materials; and computer-assisted approaches to visual ethnography. We are extending our range to quantitative approaches for assessing qualitative materials, analysing social and cultural invention, the active representation of meaning, and the applications and implications of mobile computing, sensing and communications platforms and the transformation of virtual into concrete objects, institutions and structures.

- Biological Anthropology

Biological Anthropology is the newest of the University of Kent Anthropology research disciplines. We are interested in a diverse range of research topics within biological and evolutionary anthropology. These include bioarchaeology, human reproductive strategies, hominin evolution, primate behaviour and ecology, modern human variation, cultural evolution and Palaeolithic archaeology. This work takes us to many different regions of the world (Asia, Africa, Europe, the United States), and involves collaboration with international colleagues from a number of organisations. We have a dedicated research laboratory and up-to-date computing facilities to allow research in many areas of biological anthropology.

Currently, work is being undertaken in a number of these areas, and research links have been forged with colleagues at Kent in archaeology and biosciences, as well as with those at the Powell- Cotton Museum, the Budongo Forest Project (Uganda) and University College London.

Kent Osteological Research and Analysis (KORA) offers a variety of osteological services for human remains from archaeological contexts.

Careers

Higher degrees in anthropology create opportunities in many employment sectors including academia, the civil service and non-governmental organisations through work in areas such as human rights, journalism, documentary film making, environmental conservation and international finance. An anthropology degree also develops interpersonal and intercultural skills, which make our graduates highly desirable in any profession that involves working with people from diverse backgrounds and cultures.

Many of our students go on to do PhD research. Others use their Master’s qualification in employment ranging from research in government departments to teaching to consultancy work overseas.

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As biological sciences have become more data driven, bioinformatics is now central to modern biological research, from genetics, nutrition and epidemiology to ecology, neuroscience and biomedicine. Read more

As biological sciences have become more data driven, bioinformatics is now central to modern biological research, from genetics, nutrition and epidemiology to ecology, neuroscience and biomedicine.

This programme will teach you how to manage and manipulate large datasets to reveal new insights in biological sciences. You will get intensive training in a computer-based approach to biological research, with the opportunity to develop specialist skills in computer programming, data analysis, statistics and computational biology.

New analytical techniques deliver ever more data about genes, proteins, metabolites and the interactions between them. Bioinformatics is the discipline tasked with turning all this data into useful information and new biological knowledge. With applications spanning the breadth of life science disciplines, there is now high demand for trained bioinformaticians.

Prior experience of computer programming is not required as you will be taught the latest tools and techniques in bioinformatics, which you will then apply to your own research project. You will also collaborate with peers to build new bioinformatics solutions to real-world problems as part of an innovative group project. 

This programme is delivered by academics who are actively engaged in developing bioinformatics tools and applying them in areas such as genome sequencing, proteomics, evolution, ecology, psychology, cancer, diabetes and other diseases. We have an extensive network of academic and industrial collaborators around the UK and in Europe, who contribute to teaching, co-supervise projects and provide employment opportunities.

Highlights

  • Training to manage, analyse, integrate and visualise big data using technologies such as Python and R
  • Development of skills applicable to software development, data analytics and finance
  • Delivered by academics who are actively engaged in developing bioinformatics tools and applying them in areas such as genome sequencing, proteomics, evolution, ecology, psychology, cancer, diabetes and other diseases
  • Opportunities to publish scientific papers (recent graduate had her MSc project work included in a paper published in Science)
  • Strong foundation for employment in biotechnology, life sciences and pharmaceutical sectors or PhD research

Research and teaching 

By choosing to study at a Russell Group university you will have access to excellent teaching and leading research. Our staff draw heavily upon their industrial or research council-funded research to inform their teaching and ensure projects are topical and well-resourced.

Developing bioinformatics has allowed me to work in one of the best companies when it comes to smart science. They help me understand our customers’ needs as they seek to implement bioinformatics pipelines to extract new knowledge from the data generated by our sequencers

Yasmine (Bioinformatics 2016 graduate, currently working at Illumina)

Informal enquiries 

If you have questions about this programme which you would like to put to Professor Conrad Bessant, Professor of Bioinformatics and Bioinformatics MSc Programme Director, please contact:

Tel: +44(0)207 882 6510

Email: 



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The MSc in Statistics aims to train professional statisticians for posts in industry, government, research and teaching. It also provides a suitable preparation for careers in other fields requiring a strong statistical background. Read more
The MSc in Statistics aims to train professional statisticians for posts in industry, government, research and teaching. It also provides a suitable preparation for careers in other fields requiring a strong statistical background.

*This course will be taught at the Canterbury campus*

Key benefits

- Statistics is thriving at Kent, and the research of the Group was rated in the top ten in the UK in the most recent Research Assessment Exercise. We are also one of the main hubs of the National Centre for Statistical Ecology.

- Accredited by the Royal Statistical Society (RSS)

Visit the website: https://www.kent.ac.uk/courses/postgraduate/166/statistics

Course Outline

The programme, which has recently been updated, trains professional statisticians for posts in industry, government, research and teaching. It provides a suitable preparation for careers in other fields requiring a strong statistical background. Core modules give a thorough grounding in modern statistical methods and there is the opportunity to choose additional topics to study.

Format and assessment

You undertake a substantial project in statistics, supervised by an experienced researcher. Some projects are focused on the analysis of particular complex data sets while others are more concerned with generic methodology.

You gain experience of analysing real data problems through practical classes and exercises. The programme includes training in the computer language R.

Modules:

- Stochastic Processes and Time Series (15 credits)
- Stochastic Models in Ecology and Medicine (15 credits)
- Analysis of Large Data Sets (15 credits)
- Practical Statistics and Computing (15 credits)
- Computational Statistics (15 credits)
- Project (60 credits)
- Probability and Classical Inference (15 credits)
- Advanced Regression Modelling (15 credits)
- Bayesian Statistics (15 credits)
- Principles of Data Collection (15 credits)

Assessment is through coursework and formal examinations.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

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

Why study at The University of Kent?

- Shortlisted for University of the Year 2015
- Kent has been ranked fifth out of 120 UK universities in a mock Teaching Excellence Framework (TEF) exercise modelled by Times Higher Education (THE).
- In the Research Excellence Framework (REF) 2014, Kent was ranked 17th* for research output and research intensity, in the Times Higher Education, outperforming 11 of the 24 Russell Group universities
- Over 96% of our postgraduate students who graduated in 2014 found a job or further study opportunity within six months.
Find out more: https://www.kent.ac.uk/courses/postgraduate/why/

Postgraduate scholarships and funding

We have a scholarship fund of over £9 million to support our taught and research students with their tuition fees and living costs. Find out more: https://www.kent.ac.uk/scholarships/postgraduate/

English language learning

If you need to improve your English before and during your postgraduate studies, Kent offers a range of modules and programmes in English for Academic Purposes (EAP). Find out more here: https://www.kent.ac.uk/courses/postgraduate/international/english.html

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