PhD Scholarship on Multi-criteria Decision-Making and Optimisation at the University of Manchester, UK
This PhD scholarship offers three years’ funding, including tuition fees and annual stipend of approximately £15,000 for candidates commencing their studies in September 2018. The successful candidate will receive a generous research support and conference allowance, and have access to a robust doctoral research training programme, dedicated research resources, training in transferable skills, visiting speaker seminar programme, and associate with existing research centres and groups. Students are encouraged to undertake training and development in teaching and deliver teaching/research assistantship duties on a paid basis to further enhance their experience in preparation for their future careers.
In many strategic problems in logistics, managements, planning, and manufacturing, a Decision Maker (DM) must find solutions that optimise multiple, conflicting criteria and decide among them, which nowadays often involves the DM interacting with some automated process implemented as a Multi-criteria Decision-Making and Optimisation (MCDMO) algorithm. In reality, decision-making is influenced by human factors (cognitive biases, fatigue, mistakes) that have been thoroughly studied in behavioural economics and psychology. The design of algorithms able to cope with these human factors remains an open challenge.
This project aims to devise realistic, general “simulations” of DMs (machine DMs) that explicitly model these human factors as configurable parameters, independent of specific preferences. Machine DMs will enable the empirical analysis of algorithms with respect to particular human factors. Parameters of machine DMs may be explicitly set to mimic human behaviours (e.g. risk-averse vs. risk-seeking). The ultimate goal is the development of the next generation of data analytics and decision support methods that adapt to the human factors prominent on particular problem scenarios, thus helping humans to make better decisions.
Applications are sought from exceptional UK, EU and international students with an outstanding academic background, ideally in Computer Science, Mathematics, Operations Research, Data Science, Business Analytics, Industrial Engineering, Economics, or other discipline within business and operations management. The successful candidate must have a strong programming background (C/C++/Java/R/Python) and good analytical and communication skills. An understanding of multi-criteria decision-making and/or mathematical and heuristic multi-objective optimization techniques is highly desirable.
Más información contactar a Manuel López Ibáñez (email@example.com).