(apologies for cross posting)
***** 4 fully funded PhD studentships*******
Applications are invited for 4 fully funded 3 year PhD studentships within the School of Computing. The studentship will cover tuition fees and will include a standard living allowance (stipend), (at current RCUK rate).
The studentship is expected to start in the first or second quarter of 2016. All applications must be received by 15th January 2016. Interviews will be scheduled for mid or late February 2016.
If you are successful in being shortlisted for interview you will be sent a letter of invitation by email at least 2 weeks in advance of the interview date. Those who have not be contacted by 15th February should assume that they have been unsuccessful.
The School of Computing undertakes research across a broad range of areas in computing and informatics including: bio-inspired computing; cyber-security; e-Government; e-Health; future interactions; make-believe; interactive graphics and simulation; information science; information society; information visualization; networks & distributed computing; social informatics, software engineering & systems and urban interaction design.
We have recently made significant recent investments in research and have recently recruited additional academics with strong research capabilities. Applications in the research areas in which these people have a specific interest would be particularly welcome. Areas of interest to this list incude:
** Coevolution of population structure, social behaviour, emergence of cooperation **
Projects in the broad area of evolution of cooperation within large populations
and the coevolution of population structure and social behaviour. This covers both social institutions and evolutionary robotics. Areas of interest include the origin of cooperation in large groups, the origin of sociality, the effect of individual social behaviours and group size on the emergence of population structure and cooperation. Potential applicants should have an interest in evolutionary computing, agent-based modeling.
** Hyper-heuristics and Machine Learning ***
Topics that explore the potential for machine-learning techniques to be used in conjunction with search-based optimisation techniques such as meta-heuristics or hyper-heuristics for tackling difficult optimisation problems, for example in algorithm selection, feature-mapping, tuning or algorithm design.
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For full details please see:
https://applications2.napier.ac.uk/jobvac/Jobdetails.aspx?GUID=7F88270A-F4B2-481C-A6BE-DD69BB4E8BC3
Deadline: 15th January
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