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PhD Scholarship in Global optimisation with ensemble machine learning models

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  • Full or part time
    Dr R Misener
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

The Department of Computing is a leading department of Computer Science among UK Universities, and has consistently been awarded the highest research rating from the Higher Education Funding Council. In the 2014 REF assessment, the Department was ranked third (1st in the Research Intensity table published by The Times Higher), and was rated as "Excellent" in the previous national assessment of teaching quality.

We are seeking a motivated PhD student to work on the BASF project ‘Global optimisation with ensemble machine learning models’ which is concerned with allowing state-of-the-art machine learnt models, e.g. gradient boosted trees, to be used for optimisation tasks. The algorithm(s) will be developed and improved before implementation in an open-source and user-friendly software package.

This project, a collaboration between Imperial College and the Machine Learning for Chemicals group at BASF, seeks to integrate machine learnt models into optimisation and other decision-making problems under uncertainty. The post holder will explore:

• Defining benchmark datasets to test the methods and algorithms,
• Developing the methodology for integrating these black-box models under uncertainty into larger global optimisation problems,
• Releasing all work open source and integrating it into the BASF code stack.
The post holder will work with Imperial’s Computational Optimisation Group (London, UK). The post holder may also be asked to spend 1-3 months at BASF (Ludwigshafen, DE) each year (housing arrangements to be made).
The project allows for some flexibility in the profile of applicants. Candidates with expertise in the following areas can be a good fit:

• Simulation and/or simulation-based (black box) optimisation,
• Global optimisation and/or optimisation under uncertainty,
• Open-source software development,
• Machine learning and its applications.

All applicants should be able to demonstrate the following:

• A strong computing background with solid programming skills,
• Optimisation and/or machine learning expertise,
• An ability to work with third-party software and to liaise constructively with the developers of such software,
• The ability to work independently and to drive both the research and software development agenda.

The successful applicant will have an MSc (or equivalent) in an area pertinent to the subject area.

How to apply:
Please forward your CV directly to Dr. Ruth Misener: [Email Address Removed]

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