BIO-INSPIRED COMPUTATION
The Department of Computer Science, The University of Sheffield, is
offering two Research Associate positions to work on the time complexity
analysis of bio-inspired computation techniques. The positions are part of
an EPSRC funded project entitled "Rigorous Runtime Analysis of Bio-inspired
Computing" starting on 31 March 2015 for a period of 5 years. The project
is based in the Computational Biology Group at the Department of Computer
Science and reports to Dr. Pietro Oliveto.
The Research Associates will work in a well-connected international team
with expertise in bio-inspired computing, to develop the research
objectives of the project and to contribute to its administration under the
supervision of the Principal Investigator. The Research Associates will
collaborate closely and drive the interaction with several national and
international project partners. They will also contribute to the
organisation of activities aimed at maximising the dissemination and impact
of the results as well as developing further research objectives and
contributing to future bids for research funding.
To apply you should have completed, or nearly completed, a PhD in computer
science. You should have good knowledge and strong experience of either the
theoretical analysis of bio-inspired computation techniques or of the
computational complexity analysis of problem specific deterministic and
randomized algorithms. You should have high level analytical and
computational skills and the ability to co-supervise PhD students in
bio-inspired computation.
These posts offer a competitive salary. For the duration of the project
funding is readily available for conference attendance and research visits
to partner organisations. Project partners include, amongst others,
research groups at the University of Birmingham, UK, at the Technical
University of Denmark (DTU) in Lyngby, Denmark and at the University of
Adelaide, Australia.
For further information and for submitting applications:
http://www.dcs.shef.ac.uk/people/P.Oliveto/AdvertRA.html
The full advert is available at:
http://www.dcs.shef.ac.uk/people/P.Oliveto/images/AdvertRAs.pdf
For informal enquiries:
P.Oliveto@sheffield.ac.uk
http://www.dcs.shef.ac.uk/people/P.Oliveto/
FULLY FUNDED PHD STUDENTSHIP IN TIME COMPLEXITY ANALYSIS OF BIO-INSPIRED
COMPUTATION
Applications are invited for a fully-funded PhD studentship on the runtime
analysis of bio-inspired computation techniques. The successful candidate
will join the EPSRC funded project "Rigorous Runtime Analysis of
Bio-inspired Computing" and will work alongside other researchers involved
in the project at The University of Sheffield and at project partner
organisations in UK, Europe and worldwide.
Background
Bio-inspired meta-heuristics are general purpose algorithms that mimic
powerful mechanisms from nature such as the natural evolution of species or
the collective intelligence of animals with the goal of solving complex
optimisation problems. Popular bio-inspired meta-heuristics are genetic
algorithms, ant colony optimisation and artificial immune systems. They
have been applied to a broad range of problems in various disciplines with
remarkable success. They are particularly useful in settings where no
knowledge on the problem is available (black-box optimisation) and
evaluating candidate solutions is the only means of learning about the
problem at hand. However, the reasons behind their success are often
elusive: their performance often depends crucially, and unpredictably, on
design choices and parameters. Furthermore, given a class of bio-inspired
algorithms it is unclear on which kind of problems it performs well and on
which it performs poorly. This lack of understanding represents a major
obstacle for the wide-spread uptake and usage of bio-inspired computing
techniques and for the development of more effective variants.
In recent years theoretical analyses have emerged that provide results
about the performance of bio-inspired algorithms. They rigorously estimate
the expected time required by the algorithms to find a satisfactory
solution for various optimisation problems. Such analyses use mathematical
techniques drawn and extended from the fields of randomised algorithms,
probability theory and computational complexity. The results allow for
insights into the working principles of bio-inspired meta-heuristics,
enable the assessment of parameter choices and design aspects while
contributing to the design of more powerful algorithms.
This studentship offers a valuable opportunity to work within this very
active, challenging and exciting field of research at the intersection
between computational complexity and bio-inspired computation. The
successful applicant will also have the opportunity to further develop
his/her research skills and expertise by collaborating with a wide range of
top class researchers in bio-inspired computing who are partners of the
EPSRC funded project. Project partners include, amongst others, research
groups at the University of Birmingham, UK, at the Technical University of
Denmark (DTU) in Lyngby, Denmark and at the University of Adelaide,
Australia.
The Candidate
Applicants must have at least a 2.1 or above degree in Computer Science.
Outstanding applicants from Mathematics, Physics and Engineering will also
be considered and are encouraged to apply. The successful applicant must
have excellent analytical and computational skills. He/She must be an
excellent team player who can work independently and communicate well with
others. Since the project is theoretically challenging, strong mathematical
and probability theory skills are required. Interest and enthusiasm for
bio-inspired computing are essential while experience with modern
meta-heuristics such as evolutionary algorithms and computational
complexity analyses are desirable.
The Studentship
Duration: Three years full-time (subject to satisfactory progress).
Payments: The award covers tuition fees plus a living stipend at the
standard UK research rate - currently £13,863 per annum. Funding is
available for conference attendance and research visits to partner
organisations.
Deadline: The position is available immediately and will be open until it
is filled.
How to Apply
Applicants should apply using the online application form at:
http://www.shef.ac.uk/postgraduate/research/apply
For more information on the PhD Programme at The University of Sheffield:
http://www.sheffield.ac.uk/postgraduate/research/sheffield
For further information and informal enquiries contact Dr. Pietro Oliveto at
p.oliveto@sheffield.ac.uk
http://www.dcs.shef.ac.uk/people/P.Oliveto/
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