mercredi 20 mai 2009

Research Associates in 'Optimal Collective Decision-Making in Social Insect Colonies' (Two Posts)

Applications are invited for two postdoctoral research associate (PDRA) positions to study the collective decision-making of social insects, based in the Department of Computer Science and the School of Biological Sciences, University of Bristol, and under the supervision of Dr James Marshall and Professor Nigel R. Franks, and with the collaboration of Dr Anna Dornhaus (Arizona) and Professor Tom Seeley (Cornell).
This BBSRC funded, 3-year, £500k project will build on ground-breaking work by this team in understanding how collective decision-making by rock ants and honeybees may be organised so that the resulting collective decisions are statistically optimal, representing the best possible compromise between the speed and accuracy of decision-making. The speed-accuracy trade-off in decision-making has been widely recognised in individual organisms, such as humans (Ratcliff, 1978) and bumblebees (Chittka et al., 2003) and in highly cohesive animal societies, particularly ants (Franks et al., 2003) and honeybees (Seeley & Visscher, 2004). Our recent work has been inspired by statistically optimal models of decision-making in primate neural circuits, and has shown how simple models of collective decision-making by social insect colonies can also be parameterised to implement statistically optimal decision-making (Marshall et al., 2009). This synthesis of concepts and techniques from neuroscience and insect socio-biology is one of the first studies in the rapidly emerging field of ‘Colony-Level Cognition’ (Marshall & Franks, 2009).
The current project will have experimental and theoretical strands: experiments with rock ants (Bristol) and honeybees (Arizona/Cornell) will validate existing theoretical predictions using state-of-the-art RFID tag technology, and help inform further modelling.
Two PDRA positions are open, with starting salaries up to £30,594:
1. Theoretical biologist (Department of Computer Science, University of Bristol): the ideal candidate will have a background in a numerate discipline, such as mathematics, physics, or computer science, and experience of modelling complex biological systems. Experience of some or all of stochastic ordinary differential equations, probability and statistics would be a distinct advantage. The successful candidate will work to extend the applicability of current models to more complex and biologically realistic decision-scenarios, and develop entirely new models, as well as converting their theoretical predictions into testable hypotheses for the experimental biologist (post 2) to validate. Opportunities to be closely involved in experimental design will be available, as well as to undertake some experimental work with rock ants.
2. Experimental biologist (School of Biological Sciences, University of Bristol): the ideal candidate will have a background in biological sciences; direct experience of working with social insects, especially ants and bees, would be a distinct advantage. Experience of both lab-based and field experimental work is also desirable, as are programming and data analysis skills to deal with the large volumes of data RFID experiments generate. The successful candidate will primarily undertake experimental work in the Ant Lab (Bristol) with Temnothorax albipennis, and will also undertake 3 field seasons of 3 months each to conduct emigration experiments with Apis mellifera (Arizona, with advice from Cornell). The experiments with ants and honeybees will utilise the latest RFID technology for tracking individual insects (e.g. Robinson et al. (2009)). Experimental design will be informed by the modelling predictions of the theoretical biologist (post 1), and opportunities to be involved in design of theoretical models will also be available.
References
1. Chittka, L., Dyer, A., Bock, F., Dornhaus, A. (2003) Bees trade off foraging speed for accuracy, Nature 424, 388
2. Franks, N. R., Dornhaus, A., Fitzsimmons, J. P. & Stevens, M. (2003) Speed versus accuracy in collective decision-making. Proceedings of the Royal Society B: Biological Sciences 270 (1532), 2457 - 2463
3. Marshall, J. A. R., Bogacz, R., Planqué, R., Kovacs, T. & Franks, N. R. (2009) On optimal decision making in brains and social insect colonies. Journal of the Royal Society: Interface (doi: 10.1098/rsif.2008.0511)
4. Marshall, J. A. R. & Franks, N. R. (2009) Colony-level cognition. Current Biology 19, 10 (in press)
5. Ratcliff, R. (1978) A theory of memory retrieval. Psychological Review 85, 59-108
6. Robinson, E. J. H., Smith, F. D., Sullivan, K. M. E. & Franks, N. R. (2009) Do ants make direct comparisons? Proceedings of the Royal Society Series B, (in press)
7. Seeley, T. D. & Visscher, P. K. (2004) Quorum-sensing during nest-site selection by honeybee swarms. Behavioral Ecology and Sociobiology 56, 594-601
Recent Media Coverage
1. ‘Six Legs Goods’. Guardian g2 cover feature, 9th March 2009:
Brain “Like Colony of Ants”’.
Channel4.com, 25th February 2009:
‘NIGEL FRANKS PROFILE: Watching as Ants Go Marching - and Deciding - One by One’. Science, 6th March 2009, vol. 323, pp 1284-1285.
About the Department of Computer Science
The Department of Computer Science is one of the top research-driven departments in the country. In the last HEFCE Research Assessment Exercise (2008) 70% of submitted academic staff were rated as ‘internationally excellent’ or ‘world-leading’. The Intelligent Systems group, the largest research group within the Department, explores and exploits general principles underlying learning and intelligence in machines and biological systems. It focuses on Machine Learning: software that improves with experience; Computational Biology: models of biological systems; and Bio-inspired Computation: imitating nature's solutions. The Intelligent Systems group has just been awarded a total of £1.2m in grants from the Biotechnology and Biological Sciences Research Counil, of which this project is part.
About the School of Biological Sciences
The School of Biological Sciences is a dynamic, research-based School with a commitment to fundamental biology and cutting edge advances in new technologies. In the last HEFCE Research Assessment Exercise (2008) 50% of submitted academic staff were rated as ‘internationally excellent’ or ‘world-leading’. Our research is distinctive in the range and depth of subject coverage. We have traditional strength in the biology of whole organisms and considerable expertise in the application of mathematical, molecular and biophysical methodologies to problems of behavioural, conservation, developmental, environmental and evolutionary biology. The Ant Lab has a 27 year history (18 at Bath and 9 at Bristol) of cutting edge insect research under the direction of Prof Nigel R. Franks, including 2 cover articles in Nature. Prof. Franks and the Lab were recently profiled in Science (Science (2009) Vol 323, 1284-2185).
Application Deadline
8:00 (GMT) 12th June 2009
Further Details
For informal enquiries, contact Dr James Marshall
For further details including how to apply, visit: http://www.bris.ac.uk/boris/jobs/ads?ID=80006
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James A. R. Marshall
Department of Computer Science
University of Bristol
www.cs.bris.ac.uk/~marshall