The UCL department of Chemical Engineering is one of the top research and teaching departments in the UK and has world-class standing. Within the Dept. of Chemical Engineering 90% of staff rated as world leading or of internationally excellent quality. The department has an extensive research portfolio across a wealth of areas, from molecular scale to complex systems.
Within the Product & Process Systems Engineering group, the Chemical Engineering Department is seeking an enthusiastic and dedicated post-graduate student to research how to incorporate uncertainty consideration related to the optimisation of process & energy systems engineering via novel data-driven and machine learning methods. Expertise in mathematical modelling & optimisation is essential, as well as a good understanding of machine learning techniques is desirable.
The post is fully funded (stipend and fees) for 4 years.
Please contact Dr Vasileios Charitopoulos ([email protected]
) for further details or to express an interest.
We are seeking a motivated PhD candidate to work on the project “Optimisation under uncertainty using machine learning and data-driven methods” which is concerned with developing state-of-the-art computational methods for incorporating uncertainty considerations in industrially-relevant complex optimisation problems and tools for their efficient solution.
Candidates with experience/expertise in the following areas are encouraged to apply for the studentship:
• Mathematical modelling & optimisation
• Optimisation under uncertainty
• Machine learning & data-driven modelling
The candidate will explore:
• Novel methods for modelling uncertainty considerations & propagation in multi-period optimisation problems;
• Machine learning oriented dimensionality reduction techniques;
• Mathematical programming solution methods for stochastic programming problems;
• Implementation of the aforementioned into state-of-the-art process & energy systems engineering problems.
The successful applicant will have a 1st class MSc/MEng (or equivalent) in an area pertinent to the subject area, e.g. Chemical Engineering, Operations Research, Computer Science, Mathematics.
All applicants should be able to demonstrate the following:
• A strong computing background with solid mathematical skills,
• Optimisation and/or machine learning experience,
• Advanced understanding of process and/or energy systems simulation/optimisation problems
• The ability to work independently and to drive both the research and software development agenda.