[alife] Research Associates in 'Optimal Collective Decision-Making in Social Insect Colonies' (Two Posts)
James Marshall
james.marshall at bristol.ac.uk
Mon May 18 07:25:34 PDT 2009
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Research Associates in 'Optimal Collective Decision-Making in Social
Insect Colonies' (Two Posts)
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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 n
euroscience 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 invo
lved 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: http://www.guardian.co.uk/environment/2009/mar/09/ants-nature-research
2. ‘Human Brain “Like Colony of Ants”’. Channel4.com, 25th February
2009: http://www.channel4.com/news/articles/science_technology/human+brain+like+colony+of+ants/2995692
3. ‘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
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