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(Apologies for multiple postings) Applications are invited for a full-time fixed-term (3 years) Research Fellow in Train Scheduling (Hybridised Optimisation) under the EPSRC grant EP/M007243/1 in School of Computing, University of Leeds, UK. University Grade 7 (£31,342 - £37,394 p.a.) The aim of the project is to derive efficient practical methods for producing train unit schedules that are operable in real life practice. Efficient passenger rail, critical to the UK economy, requires optimised operations planning. Well before a timetable goes live, train unit scheduling is part of resource planning as to how the daily train services would be covered. A train unit is assigned a sequence of timetabled journeys ensuring all the connections are feasible, both in terms of time and physical constraints. The problem is like an enormous jigsaw puzzle balancing between minimising the train unit resources and satisfying passenger demands and operational constraints. This project builds on successful research collaboration with First ScotRail and Tracsis Plc. The planned research is grounded on an exact mathematical approach. While the mathematical approach has superior optimisation power, computational time escalates exponentially to becoming impractical beyond small to medium sized problem instances. You will investigate a new method that could make a step change. Recognising that there is a practical limit on how large a problem instance the mathematical optimiser can solve 'comfortably' a heuristics is used to compress and transform the problem instance into a much smaller one for the mathematical solver to be applied. Over a number of cycles, more and more is learnt about the key data points to be retained in the compressed instance whereby the hybridised algorithm would converge to the optimal or very near optimal solution. The above work will be interacting with that of another Research Fellow employed on this project, who will mainly investigate improving especially in terms of computational performance the core mathematical solver. Furthermore, both Research Fellows will be engaged in activities with our industrial collaborators to ensure that the most realistic model is built, the solution schedules produced are fully operable and testing and evaluation are as thorough as possible. The activities include short placements, regular contacts, on-site testing/evaluation and three seminar workshops that other train companies will also be invited to. The successful candidate will have a PhD or near completion of a PhD in a relevant subject (including, but not limited to, scheduling, combinatorial optimisation, meta-heuristics search and computer science); a track record in the design and implementation of meta-heuristics search algorithms for practical problem solving; programming skills for algorithmic and multi-threaded software development (C++, C). Application and further details at: https://jobs.leeds.ac.uk/vacancy.aspx?ref=ENGCP1003 Closing date: Thursday 20 November 2014 Informal enquires to Dr Raymond Kwan, Senior Lecturer, tel +44 (0)113 343 5760, email [log in to unmask]<mailto:[log in to unmask]>