Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

  Sequential stochastic optimisation problems


   School of Mathematical Sciences

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof A Gnedin  Applications accepted all year round  Awaiting Funding Decision/Possible External Funding

About the Project

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2016 (funded students) or at any point in the academic year (self-funded students).
In many real-life decision situations the inputs are known only with associated uncertainty. What is the optimal moment to buy or sell an asset? When should one stop searching for new species? How to sort the data without having the entire input available from the start? How to minimise losses in clinical trials, when different treatment need to be experimented?

Markovian sequential optimisation problems are mathematical models for such online decision processes. Each action of the decision-maker has both immediate and long-term consequences, which must be taken into account to achieve optimality over all stages of the decision process. For instance, in the classical best-choice problem the objective is to stop at the item best in a random sequence. Having observed an item, the decision-maker faces the dilemma: the choice candidate which looks best so far may turn not the best overall, but if the item is rejected it will not be available in the future.

This project aims to study features of efficient sequential decision strategies in combinatorial optimisation problems. Apart from the maximising the expected reward issue, the focus is also on other performance measures and features of the decision policies, as well as on their connection and robustness with respect to distinct optimality criteria.

This project will be supervised by Professor Alexander Gnedin.

The application procedure is described on the School website. For further enquiries please contact Prof Alexander Gnedin ([Email Address Removed]).

This project is eligible for several sources of full funding for the 2016/17 academic year, including support for 3.5 years’ study, additional funds for conference and research visits and funding for relevant IT needs. Applicants interested in the full funding will have to participate in a highly competitive selection process. The best candidates will be eligible to receive a prestigious Ian Macdonald Postgraduate Award of £1000, for which you will be considered alongside your application. The application deadline for full funding is January 31st 2016.

There is also 50% funding scheme available for students who are able to find the matching 50 % of the cost of their studies. Competition for these half-funded slots will be less intensive, and eligible students should mention their willingness to be considered for them in their application. The application deadline for 50 % funding is January 31st 2016.

This project can be also undertaken as a self-funded project, either through your own funds or through a body external to Queen Mary University of London. Self-funded applications are accepted year-round.


Funding Notes

If you wish to apply, please visit the application website and mention that you wish to work on the “Sequential stochastic optimisation problems” project.

School website: http://www.qmul.ac.uk/postgraduate/research/subjects/mathematical-sciences/index.html

How good is research at Queen Mary University of London in Mathematical Sciences?


Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities