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Automatisation of optimisation problem formulation for real-world applications

With the current development of AI and Big Data, there is a strong need in the development of the approach that allows the efficient mapping of the existing data into the optimisation problem. At the moment there is a gap that requires significant understanding and development of new methodological approaches that will allow one to provide the connection gap between existing data and problem definition.

The project will include the formulation of the approach on effective mapping of existing data and problem optimisation. The skills required by the potential applicants are good skills in object-oriented programming, skills in analytical analysis. The knowledge of AI techniques is preferable.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.