Hyper-heuristics for Grouping Problems
University of Nottingham - School of Computer Science
http://jobs.nottingham.ac.uk/vacancies.aspx?cat=345#j7933
This studentship is associated with The LANCS Initiative (see:
http://www.lancs-initiative.ac.uk/), particularly systems to build systems
research cluster. The successful student will join the Automated Scheduling,
OptimisAtion and Planning (ASAP) research group (see:
http://www.asap.cs.nott.ac.uk/) and have the opportunity to interact with
the leading scientists in the field. Most of the existing decision support
systems are developed based on expert knowledge and they are custom made for
a given problem solving environment. On the other hand, there is an emerging
class of intelligent methodologies that allow decision support systems
to
learn, adapt and improve their behavior, and/or their structure
automatically to accommodate complexities of real world problems. These
methodologies are applicable to different problem domains and aim to
raise
the level of generality by selecting and/or generating new methodologies
automatically during the search process. This exciting research area
lies at
the interface between operational research and computer science and
involves
understanding of representational issues, decision making mechanisms and
learning, design, implementation and analysis of hyper-heuristics. The
application domains will be cross disciplinary focusing on grouping
problems.
ASAP is one of four main research groups within the School of Computer
Science at Nottingham. ASAP has been carrying out innovative research
into
the development and investigation of decision support, search
methodologies
and machine learning for a wide and diverse range of real world problem
environments for the last decade. The group comprises 12 members of
academic staff, 19 researchers, 48 PhD students and three
administrators.
Students should have an undergraduate or Masters Degree in computer
science,
operational research, mathematics or closely related area or at least an
upper second-class honours degree (ideally a first class degree), or a
combination of qualifications and/or experience equivalent to that
level.
Knowledge of computational complexity theory, single and multi-objective
optimisation methodologies and machine learning is extremely desirable.
Students with a mathematical background, if they have good programming
experience, are also encouraged to apply.
This studentship is available for 3.5 years and includes an approximate
maintenance grant of GBP 13,300 per year, maintenance grant and UK/EU
tuition
fees.
Informal enquiries may be addressed to Dr E Ozcan, Email:
exo@cs.nott.ac.uk.
Please note that applications sent directly to this email address will
not
be accepted.
To apply, please access:
http://pgstudy.nottingham.ac.uk/apply-for-postgraduate-courses.aspx.
Please quote ref. SCI/879. Closing date: Open until filled.
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