The goal of the Computational Science Lab is to tackle fundamental problems in science in areas of societal importance, by bringing together new kinds of scientists, in a new kind of Laboratory, pioneering new kinds of approaches, new kinds of computational methods, and new kinds of scientific software tools.
Biological Computation GroupThe Group is focused on the development and advancement of a new field of Biological Computation, that aims to transform our understanding of biology by considering biological systems as living computation, and to develop the techniques needed to design and program computation in living systems.
Computational Ecology and Environmental Science GroupThe Group is focused on enabling, making and accelerating fundamental advances in our understanding of, and ability to predict the impact of future changes to, the global climate and ecological systems and processes: Earth’s life support system.
In the News
LATEST: 17 January 2013. Time to model all life on Earth. Paper setting out the scientific and policy making importance of a General Ecosystem Model and our researh into the development of such a model, published in Nature by Drew Purves et al.
11 September 2012. Microsoft and IUCN form unique partnership to tackle species extinction.
- Boyan Yordanov, Christoph M. Wintersteiger, Youssef Hamadi, and Hillel Kugler, SMT-based Analysis of Biological Computation, in NASA Formal Methods Symposium 2013, Springer Verlag, May 2013
- Cory Merow, John A. Silander, and Matthew J. Smith, A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter, in Ecography, Wiley, April 2013
- K. M. Young, K. Psachoulia, R. B. Tripathi, S-J. Dunn, L. Cossell, D. Attwell, K. Tohyama, and W. D. Richardson, Oligodendrocyte dynamics in the healthy adult CNS: evidence for myelin remodelling, in Neuron, 6 March 2013
- Maurizio Sajeva, Claudio Augugliaro, Matthew Smith, and Elisabetta Oddo, Regulating Internet Trade in CITES Species, in Conservation Biology, Wiley, 8 February 2013
- Mindy M. Syfert, Matthew J. Smith, and David A. Coomes, The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models , in PLOS One, vol. 8, no. 2, PLoS, February 2013
Biological Computation Group
Head: Andrew Phillips
Adminstrator: Hayley Thurgood
Computational Science Laboratory
7 JJ Thomson Avenue
Cambridge CB3 0FB
+44 (0)1223 479 878
Computational Ecology & Environmental Science Group
Head: Drew Purves
- We are currently looking for outstanding scientists both for permanent and post-doctoral positions in the Biological Computation Group and in the Computational Ecology & Environmental Science Group