Contacts

Course director

Dr Samraat Pawar

Course co-director

Dr James Rosindell

Course Administrator

Mrs Amanda Ellis

Course overview

This course is for students with a passion for biology, who wish to be trained in cutting-edge quantitative techniques in ecology, evolution and conservation.

 Key Facts

  • This course combines the best features of two former courses: Quantitative Biology MSc (QB) and Biodiversity Informatics and Genomics MRes (BIG)
  • Quantitative skills are a critical limiting factor in modern biology, including the fields of Ecology, Evolution, Behavior and Conservation Biology
  • In this course students learn those skills in application to important biological problems in one of the world's leading institutions for quantitative biology
  • Students leave with skills in computing, statistics, and mathematical modelling that give them a major edge in competing for PhDs and jobs
  • Of 22 students in the class of 2014-15, 76% have already got placements, including  15 PhDs, at Oxford, Cambridge, Trinity College Dublin, Cork, Sheffield, and Imperial College London. Similar success rates from previous batches.
  • The course is suitable for students from life, physical, computer as well as mathematical sciences backgrounds
  • Computational tools are biology's next microscope, only better - learn to use them now!

Overview

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, J.E., 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, J.E., PloS Biology, 2004) because biology will in turn continue to spur major new developments in computation, mathematics and statistics, just as physics has done. In this unique course, we teach quantitative methods and biological concepts together, through application of the methods to contemporary biological research problems.

Key features of the course:

  • The course is team-taught by theoretical and empirical biologists.
  • Each student gets a hi-spec linux laptop for the course duration.
  • You will be immersed in a collaborative learning environment, consistent with the interdisciplinary nature of modern biology.
  • 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.
  • Mathematical, statistical, and computing tools are learned through application.
  • The course comprises a taught component including core computing and statistical modules, and a research project lasting about 5.5 (MSc) or 9 (MRes) months.
  • The research project can be supervised by multi-disciplinary Imperial College faculty (across departments and campuses), or through links to a number of outside institutes including Kew Botanical Gardens, the Natural History Museum, Centre for the Environment, Fisheries and Aquaculture Science, and the Institute of Zoology.

Modules in the taught component of the course include:

  • Foundational topics in computing with the powerful combination of Python & R  
  • Scientific data management in the Unix environment
  • Numerical programming in biology
  • Advanced and parallel computing in biology
  • Spatial analyses and Geographical Information Systems (GIS)
  • Eco-evolutionary dynamics and demography
  • Population genetics and genomics
  • Modelling complex communities and ecological networks
  • Inference of biological mechanisms from temporal or spatial data
  • Microbial diversity, molecular ecology
  • Maximum likelihood and Bayesian methods
  • Generalized linear modelling in biology

More information

Student comments

'The CMEE course is an excellent choice for anyone looking for a career, in academia or industry, as a quantitative biologist. The Msc course has given me a lot of computational experience and a good idea of what PhD research will entail. I also think Silwood park has one of the most friendly and close-knit academic communities.' - Matishalin Patel, Class of 2014-15. Mat started a PhD at Oxford in the Interdisciplinary Bioscience DTP.

'The MSc in CMEE allowed me to combine two of my key interests, biology and maths, while also allowing me to develop new skills such as computer programming and modelling. I could then put these skills into practice during my research project in Iceland, from data collection right through to analysis, which was hugely satisfying.  The CMEE course puts you in a fantastic place for beginning a research career' - Louise Archer, Class of 2014-15. Louise started a PhD with Tom Reed at University College Cork, Ireland on evolution and ecology of alternative life histories in brown trout. 

'Biologists who possess mathematical and computational skills are becoming increasingly popular with potential supervisors and employers; Quantitative Biology is therefore the perfect stepping stone.' - Rebecca Spriggs, class of 2011, became a PhD student in the laboratory of David Coomes, Department of Plant Sciences, Cambridge University.

CMEE class of 2014-15
Some of the classy CMEE class of 2014-15 doing their thing

'This course helped me bring several interests together in preparation for a PhD. A fantastic opportunity for all biology students looking to develop.” – Sean Tuck, class of 2012. Sean was accepted to become a PhD student in laboratory of Andy Hector, Oxford University.

'As a student coming from a mathematical background the course helped me widen my scientific horizons and interests on topics that I previously had never considered.’ – Dimitrios Nerantzis, class of 2011, became a PhD student in the laboratory of Claire Adjiman, Department of Chemical Engineering, Imperial College London.

"The Quantitative Biology MSc provided me with a set of skills which I find to be applicable in all fields of biology. It taught me how to create models of biological processes and use these models to make predictions. I also developed programming skills and learnt how to analyse data. These are critical skills in research." - Carolina Feijao, class of 2011, became a PhD student in the laboratory of Paul Dupree, Department of Biochemistry, Cambridge University.

‘I always had help and guidance from the instructors, and by the end of the year I was able to do quite complex analyses in R. Modelling and analytic concepts are taught from a biological perspective, with practical applications of theoretical concepts. I would really recommend the MSc in Quantitative Biology to any biologist with an interest in modelling. I believe it coulhelped me to become a better researcher.’ – Michela Busana, class of 2012, became a PhD student in a joint studentship between the University of Sheffield and the University of Groningen.

“The quantitative biology masters provided a great transition from my mathematics undergraduate into the field of biology.  Small class sizes allow for one on one tutoring between Lecturers and students which is essential for inter-disciplinary research.  The course covers all the fundamental techniques required for modern day biological research and there is not a better grounding to have when applying for PhDs.” – Jack Massey, class of 2011, became a PhD student in the laboratory of Tim Coulson, Oxford University.

‘In one year, I learnt a multitude of techniques that have all proven to be invaluable in my PhD.  I had always been interested in mathematical inte rp retat io ns of biological sy stems, but the QB course introduced me to programming these models, which I enjoyed so much it is now a major compone nt of my research.’  - Rebecca Spriggs, class of 2011, became a PhD student in the laboratory of David Coomes, Department of Plant Sciences, Cambridge University.

"The course unites great teaching staff with relevant, modern and interesting courses. I have learned much from it and I believe that anyone interested in applying mathematical and computational tools to biological questions would benefit from it greatly. During this one year I was in contact with great researchers and students and I am certain that this has helped me in my career." - Ana Gomez, class of 2012.

"Coming from an ecology background, this course expanded my skill-set hugely, giving me the ability to comprehend, question and perform modern, high-standard research in ecology and evolution. Also, the mathematical, computational and general research skills acquired are highly transferable." - Paul Rassell, class of 2012, became a PhD student in the laboratory of Daniel Reuman, Division of Ecology and Evolution, Imperial College London.

Project examples

The effects of environmental temperature and thermal adaptation on predator-prey interactions. 2015, Louise Archer. Louise started a PhD with Tom Reed at University College Cork, Ireland on evolution and ecology of alternative life histories in brown trout. 

Assessing general models for the temperature dependence of population density in disease vectors. 2015, Tom Smallwood. Tom started a PhD on the ecology of infectious diseases with Rosie Woodroffe at ZSL.

Why Do Whales Exist?: An Investigation into Cancer Resistance in Cetaceans. 2015, Matthew Speight.Matthew Started  a PhD in Interdisciplinary Biosciences at Oxford University.

Linking the Impact of Selective Logging with Seedling Recruitment Dyanmics. 2015, Michael Massam. Michael started a PhD in the Edwards lab at Sheffield University on optimising logging strategies in the Brazilian Amazon to minimise biodiversity loss. 

Modelling the relationship between local biodiversity and remotely-sensed vegetation indices: the effect of spatio-temporal scale. 2012, Sean Tuck. Sean was accepted to become a PhD student in the laboratory of Andy Hector, Oxford University. Also see MODISTools: an R package for retrieval and processing of remote-sensing data from NASAs MODIS satellites

Finding value in SAD moments: a novel approach to upscaling species-abundance dsitributions. 2012. Hercules Araclides. Hercules was accepted to become a PhD student, beginning September 2012,  in the laboratories of Pierre Legendre, University of Montreal, and Jonathan Davies, McGill University, Canada.

Eco-evolutionary dynamics in the bighorn sheep: linking populaton growth, trait variation and heritability of body mass. 2012. Michela Busana. Michela became a PhD student in a joint studentship between the University of Sheffield and the University of Groningen

Investigating climate change extinction risks of amphibians by simulation: the importance of life history and thermal performance traits. 2012. Bonnie Mappin. Bonnie became a Research Assistant in the laboratory of Simon Hay, Spatial Ecology and Epidemiology Group, Department of Zoology, Oxford University. She is working on the Malaria Atlas Project.

Testing for a random walk hypothesis with or without measurement error. 2012. Tin-Yu Hui. Tin-Yu became a PhD student in the laboratory of Austin Burt, Division of Ecology and Evolution, Imperial College London.

Modelling the impact of a keystone species on community diversity and stability. 2012. Jon Hamley. Jon became a PhD student in the laboratory of Jacob Koella, University of Neuchatel.

Survival of an exploited grey wolf population in the Northern Rocky Mountains: density dependence and licensed huntng. 2011. Jack Massey. Jack became a PhD student in the laboratory of Tim Coulson, Oxford University.

Demographic and evolutionary implications of lion body size: the application of an integral projection model to a large carnivore. 2011. Rebecca Spriggs. Rebecca became a PhD student in the laboratory of David Coomes, Department of Plant Sciences, Cambridge University.

Predicting induced chaos in the population dynamics of an insect species. 2011. Dimitrios Nerantzis. Dimitrios became a PhD student in the laboratory of Claire Adjiman, Department of Chemical Engineering, Imperial College London.

A synergy between wild and commercial: bio-economic modelling of python farming. 2011. Carolina Feijao. Carolina became a PhD student in the laboratory of Paul Dupree, Department of Biochemistry, Cambridge University.

Teaching staff

In addition, guest lectures and modules on specialized topics are delivered by members from the Maths, Engineering and Computer Science Departments at Imperial College, including the Centre for Complexity Science

How to apply

All applications to the programme must be made online through the Imperial College applicatin site. You should read the application instructions carefully before submitting your application. For additional information on how to apply please contact the Postgraduate Administrator; telephone +44 (0)20 7594 2251; email amanda.ellis@imperial.ac.uk.

Links with Employers

Imperial College works closely with employers and industry, including Industrial Advisory Panels to design Master’s courses which provide graduates with technical knowledge, expertise and transferable skills and to encourage students to take internships and placements. All Master’s courses are designed with employer needs in mind with some Master’s courses accredited by Professional, Statutory and Regulatory Bodies. Most Master’s courses offer an opportunity to carry out research projects in industry.

Entry Requirements & Fees

The course is open to students with a broad range of biological degrees including biology, zoology, plant sciences, microbiology and environmental sciences, as well as bioinformatics, engineering, mathematics, computer science, or physical sciences. The minimum expected requirement is an Upper Second Class Honours degree in a relevant subject from a UK academic institution, or an equivalent overseas qualification. A minimum of a grade B within A level Mathematics, or a degree demonstrating requisite knowledge of maths is also required.

Applicants must also meet the College's English language requirements which for students outside the English speaking world are: IELTS 6.5 (plus writing and speaking 6.0); TOEFL Internet 100 (plus writing and speaking 24).