Stochastic models for dynamic resource allocation

Consider a scenario in which a company has a range of Research and Development projects in which it could invest over time. 

The successful prosecution of each project requires the commitment of scarce resources (manpower, money). The projects themselves evolve over time and those which had initially appeared very promising (and worthy of considerable investment) may ultimately prove less so. We shall consider approaches to the development of policies for the dynamic allocation of key resources in such environments. Traditional approaches based on dynamic programming cannot deal with the complexity and size of realistic systems and we seek effective alternatives.

A doctoral student is sought who has a first degree with a substantial quantitative component. A preparedness to develop computer programming skills is essential and training will be given as necessary.

Further particulars from the supervisor, Kevin Glazebrook, Chris Kirkbride or Peter Jacko.

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