MSc in Computational Methods in Ecology and Evolution
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.
In this unique course we teach quantitative methods and biological concepts together, through application of the methods to cutting-edge biological research problems.
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
The course serves as ideal preparation for either PhD studies or employment in fields of applied quantitative biology, such as resource management and conservation.
This course provides the combination of biological and quantitative skills necessary for students to address modern and pressingly important questions in biological research, conservation, management, and other applications. The course is structured around cutting-edge questions such as:
- How do ecology and evolution interact in the face of a changing climate?
- How do we infer the mechanisms driving population dynamics from limited data?
- How do we predict the likely effects of human disturbances such as climate change?
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.
The course comprises a taught component, and a research project lasting about six months. The project can be supervised by staff members from Imperial College or a number of outside institutes with which we have collaborative links (including Kew Botanical Gardens, the Centre for the Environment, Fisheries and Aquaculture Science, and the Institute of Zoology).
Modules in the taught component of the course currently include:
- GIS in application to global biodiversity conservation
- The R programming language in application to population dynamics
- Molecular ecology
- Maximum likelihood in biology
- Modelling complex communities
Minimum academic requirement
2.1 Honours degree in a biological, ecological, or other life sciences subject, or in a physical sciences subject, and an A-level in mathematics.
The academic requirement above is for applicants who hold or who are working towards a UK qualification.
We also accept a wide variety of international qualifications.
English language requirements
All candidates must demonstrate a minimum level of English language proficiency for admission to the College.
For admission to this course, you must achieve the standard College requirement in the appropriate English language qualification.
This school offers programs in:
Last updated November 17, 2015