[Neuroinfo] hD Studentship on ‘GPU-Accelerated Computational Modelling and Simulation of Large-scale Biologically Realistic Models of the Fruit Fly Brain’

[Paul Richmond]

Applications are invited for a PhD studentship starting in September 2016,
which is aligned to the Digital Fruit Fly Brain project, a flagship
research project funded by BBSRC and NSF. The project is led by the Centre
for Signal Processing and Complex Systems (
http://www.sheffield.ac.uk/acse/spcs) at University of Sheffield and by the
Bionet Group at Columbia University (http://www.bionet.ee.columbia.edu/) in
collaboration with a number of research laboratories in UK, US and Taiwan
and supported by NVIDIA Corporation. The overall aim of the project is to
design, implement and experimentally evaluate a potentially transformative
open-source fly brain simulation platform capable of simulating ~135,000
neurons that make up the adult Drosophila brain. This computational
infrastructure will be based on the recently established GPU-enabled
Neurokernel software platform (https://neurokernel.github.io/). The modular
simulation platform will integrate all knowledge about the Drosophila brain
as a set of interconnected simulation modules which describe the operation
of about 41 Local Processing Units (LPUs), 6 hubs and their
interconnections, partly elucidated by detailed EM imaging studies. The
simulation platform will be used to develop and validate a first draft
model that incorporates the most advanced biophysical and/or functional
models of the neurons and the latest published synaptic connections maps.

The focus of the PhD project is on the development of highly scalable
algorithms that exploit the parallel processing power of multi-GPU systems
to enable reverse-engineering and simulation of increasingly complex,
large-scale, biologically realistic models of the fly brain using the
Neurokernel platform. This will involve the development of methods and
algorithms for neural modelling and data assimilation, mapping the
computational models on large GPU clusters and adaptive load balancing. The
project will offer the opportunity to work alongside other full time
research staff as well as interacting with research teams from around the
world.

The PhD student will work under the supervision of Dr Paul Richmond from
the Department of Computer Science and Prof Daniel Coca from the Department
of Automatic Control & Systems Engineering. The candidate will work
alongside a team of three Research Associates already appointed.

Candidates must have an excellent first degree in Computer Science,
Electrical/Control Engineering or a closely related subject and have
excellent programming skills. Some prior experience of GPU programming or
performance oriented computing is highly desirable. Previous experience in
biological modelling, numerical simulation of complex systems, dynamical
systems, would be an advantage.

Potential candidates are welcome to discuss their application informally
with Dr Paul Richmond (p.richmond at sheffield.ac.uk)

Applicants should apply using the Apply button below or online at:
http://www.sheffield.ac.uk/postgraduate/research/apply/applying
<http://www.sheffield.ac.uk/postgraduate/research/apply/applying>

*Funding Notes*

This Studentship will cover tuition fees at the UK/EU rate and provide a
tax-free stipend at the standard UK Research Council rate (currently
£14,057pa) for three years.

-- 
Dr Paul Richmond (Research Fellow) - University of Sheffield
http://www.paulrichmond.staff.shef.ac.uk
p.richmond at sheffield.ac.uk

Department of Computer Science <http://www.sheffield.ac.uk/dcs>
Sheffield NVIDIA CUDA Research Centre
<http://gpucomputing.sites.sheffield.ac.uk/>
Advanced Computing Research Centre <http://www.acrc.com>
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