DIAMOND studentships

Eight fully funded PhD studentships in Operational Research, Data Science, and Mathematical Modeling.
The Southampton initiative “from Data and Intelligence via ModelliNg to Decisions” (DIAMOND) invites applications for their fully funded PhD studentships. DIAMOND is run jointly by Mathematical Sciences of the University of Southampton and the Southampton Business School. It offers graduate students an intensive training and research programme that equips them with the skills needed to tackle modern problems in Operational Research, Data Science, and mathematical modeling.
This year, DIAMOND offers eight fully funded studentships to strongly motivated students. Scholarships will be awarded on a competitive basis. Applicants should have or expect to obtain the equivalent of a UK first class or upper second class honours degree (and preferably a master’s degree) in mathematics, computer science, engineering or other relevant discipline. The studentship provides a maintenance grant at the Research Council UK rate and tuition fees at the UK/EU rate. Applications should include a cover letter, CV, detailed academic transcripts and the contact details for at least two academic referees.
We presently offer the following projects, all sponsored by our industrial partners

• Analytics for condition based maintenance. Sponsored by Siemens UK, this project will focus on developing a combination of data- and model-driven approaches to support the condition based maintenance of rolling stock equipment.
• Exploiting symmetries for network control. Network control involves the identification of an optimal set of driver nodes, such that the given system can be steered in a desired direction. Identifying such nodes poses an extremely difficult optimization problem in practical applications. In this project we will develop algorithms and techniques to solve network control problems exploiting recent results on network symmetries.
• Global supply chain and resource management for aircraft fleets in uncertain environments. We will develop novel mathematical models and optimisation algorithms for joint supply chain and resource management in an uncertain environment. Working closely with the project sponsor Boeing Defense UK, you will create mathematical tools that support decision makers in maintaining flexibility and robustness in resource management to meet an increasing variety of expectations in a dynamic environment.
• Maximising the throughput of production and assembly lines using symbiotic simulation optimisation. Working with Ford motor company’s Powertrain Manufacturing Engineering department, this project will realise the full benefits of Industry 4.0 on increasing manufacturing throughput through developing novel optimization via simulation techniques that work with symbiotic simulations.
• Optimal Control of Autonomous Vehicles in Highly Dynamic Environments. Sponsored by Northrop Grumman, you will consider mathematical models and computational tools for robust control of swarms of autonomous vehicles in highly dynamic environments.
• Predictive maintenance through advanced data exploitation. Based on advanced machine learning concepts, we want to develop predictive maintenance tools for fleets of vehicles. The industrial project sponsor provides a data analytics capability for an advanced Health and Usage Monitoring System whereby sensors record hundreds of parameters per second and thousands of fault codes and user notifications.
• Random forests for noisy applications in finance. In the financial and insurance sector, machine learning ML challenges usually arise either in a setting where data is contaminated by noise or the model to be learned is of a stochastic nature. In close collaboration with our partner DEVnet, we will investigate selected variants of regression trees
• Reliability Analytics. : This project will focus on developing approaches to reliability modelling of key Rolling Stock components based on Siemens Maintenance Management System and Train Diagnostic data.

Students will be part of the vibrant research environment of CORMSIS, the Centre for Operational Research, Management Science, and Information Systems. CORMSIS at the University of Southampton has an established breadth and depth in Operational Research unrivalled in the UK. Our research centre applies advanced mathematical and analytical modelling to help people and organisations make better decisions. CORMSIS is the largest Operational Research group in the UK, spanning Mathematical Sciences and Southampton Business School. Among the many areas of expertise, it has extensive breadth and depth of experience in mathematical modelling and optimisation, but covers the whole spectrum of current OR/MS/IS from mathematical optimisation through business analytics and simulation to qualitative research in problem structuring.. In the QS World Rankings by Subject 2019, Operational Research and Statistics at the University of Southampton are placed at 48th in the world and 7th in the UK.

See http://www.southampton.ac.uk/cormsis/ for further details.
Application deadlines:
For the project ‘Maximising the throughput of production and assembly lines using symbiotic simulation optimisation’: 30 June 2019.
All other projects: 15 July 2019.
How to apply:
Please have a look at
https://www.southampton.ac.uk/maths/postgraduate/research_degrees/apply.page
For informal discussions please contact Professor Joerg Fliege, J.Fliege@soton.ac.uk