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PhD Studentship
Title: Computational Search Methods for Mixing Online & Offline Optimisation
University of Nottingham - School of Computer Science
This project is motivated by real-world situations that require some
immediate (online) decision making, but have aspects requiring (offline)
planning over a longer time period. A particular focus of interest will
be that of the management of a hospital emergency room. As patients
arrive, then decisions need to be made immediately. Conversely, staffing
decisions, such as which nurses work on which shifts, can be made weeks
in advance (offline). The challenge in this case is to design a system
so that these online and offline decision making processes work
efficiently and effectively together. As far as possible, patients
should get rapid treatment, but also staffing costs should be reduced,
and nurses should have working times matching their preferences. This is
a computationally challenging problem (e.g. NP-hard), but of practical
interest in many real-world situations. This project will investigate
automated decision making processes that effectively handle the
interactions between the online and offline decision making. It will
develop appropriate computational search methods, and ultimately combine
together queuing networks (e.g. using simulation) and combinatorial
optimisation, so as to solve real-world problems. The mix of online and
offline will place it in an exciting and relatively unexplored area of
computer science and operational research.
Students should have at least an upper second-class honours degree
(ideally a first class degree), in computer science, mathematics,
operational research, management science (with a substantial mathematics
component), or related area, or a combination of qualifications and/or
experience equivalent to that level. Good programming ability is
required. Students with a mathematical background, if they have
programming experience, are encouraged to apply. Knowledge of one or
more of computational complexity theory, heuristic and exact search
methods, mathematical programming, and stochastic processes (such as
queuing theory or Markov chains), is also desirable, though the main
requirement is good analytical thinking.
This studentship will allow the student to be associated with The LANCS
Initiative (see: http://www.lancs-initiative.ac.uk/), and particularly
the 'Heuristic understanding' and "Systems to build systems" research
clusters. 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. ASAP is one of five 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 8 members of academic staff, 7
researchers, 37 PhD students and 1 administrator.
This studentship is available for 3½ years and includes an approximate
maintenance grant of £13,300 per year, maintenance grant and UK/EU
tuition fees. Due to funding restrictions, this studentship is only open
to UK students.
Informal enquiries are welcome and may be addressed to Dr Andrew Parkes,
see: http://www.cs.nott.ac.uk/~ajp/ or Email: [log in to unmask]
However, 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/1101. Closing date: The initial deadline is 9
Feburary 2012, though the position will remain open until filled.
For all our vacancies and more about working at the University of
Nottingham see: http://jobs.nottingham.ac.uk/.
regards,
Andrew Parkes
http://www.cs.nott.ac.uk/~ajp/
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