Coventry University Featured PhD Programmes
Heriot-Watt University Featured PhD Programmes
University of Exeter Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
University College London Featured PhD Programmes

Optimisation Under Uncertainty Using Machine Learning & Data-Driven Methods

  • Full or part time
  • Application Deadline
    Tuesday, March 31, 2020
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

VACANCY INFORMATION

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 () for further details or to express an interest.

STUDENTSHIP DESCRIPTION:

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.

PERSON SPECIFICATION

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.

Funding Notes

ELIGIBILITY

First-class degree at the MEng/MSc or EU equivalent level is required.
Funds are only available to cover EU/UK fees.

Stipend: £17,264 per annum + UK/EU fees

Start date: the successful candidate is expected to start on 01/10/2020

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2020
All rights reserved.