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PhD Studentship: Creating algorithms for optimal process design in dynamic large-scale systems with surrogates


   Department of Chemical and Process Engineering

  Dr Michael Short,  Monday, January 31, 2022  Funded PhD Project (Students Worldwide)

Guildford United Kingdom Applied Mathematics Chemical Engineering Computational Mathematics Energy Technologies Engineering Mathematics Machine Learning Mathematical Modelling Operational Research Software Engineering Systems Engineering

About the Project

As nations start acting on their commitments towards decarbonised economies, there is an increasing need for new energy-efficient, carbon neutral processes and products. With high renewable energy penetration, these processes will likely need to be dynamic, distributed, and able to respond to rapid changes in market. Due to the complexity and novelty of these systems, new computational methods are required to screen and evaluate potential process networks systematically and efficiently and balance technoeconomic and environmental trade-offs.

In this project, we will develop novel algorithms and workflows for process design and optimisation, combining state-of-the-art mixed integer nonlinear programming optimisation approaches with surrogate modelling to identify key bottlenecks and barriers to developing profitable green processes. The algorithms developed could be used both during early and later technology readiness levels for the given process and will include multiple timescales and decision-making under uncertainty. There will be opportunities to collaborate with world-class researchers at other leading academic institutions, as well as with our industrial partners.

We are seeking enthusiastic and motivated applicants with an interest in computational optimisation and process systems engineering. A degree in Chemical Engineering, Computer Science, Mathematics or other engineering/science disciplines with significant computational elements, and some coding experience in a programming language (e.g., Python, GAMS, MATLAB, or Julia) are essential for the role. Experience in mathematical optimisation modelling, open-source software, and/or process simulation is desirable.

The successful candidate will be supervised by Dr Michael Short and Prof Tao Chen and will be based at the Department of Chemical and Process Engineering. The department has a long history of excellence in computational and process systems research. We have a vibrant, interdisciplinary group of researchers working in a variety of areas to solve global problems in pharmaceuticals, energy, wastewater treatment, and catalysis. The Information and Process Systems Engineering Research Theme holds regular research seminars and social events to provide a supportive and friendly team atmosphere. You will receive comprehensive research training and opportunities to participate in conferences, workshops, and seminars to develop professional skills and research network.

Initially offered for an April 2022 start, but later start dates can be considered.

Entry requirements

Applicants are expected to hold a first or upper-second class degree in a relevant discipline (or equivalent overseas qualification), or a lower second plus a good Masters degree (distinction normally required).

English language requirements: IELTS score of 6.5 or above (or equivalent) with 6.0 in each individual category.

How to apply

To apply, please send your CV and cover letter to Dr Michael Short () and start an application via the process through the Chemical and Process Engineering PhD programme page. Please clearly state the studentship title and supervisor on your application.


Funding Notes

Full tuition fee waiver p.a. (UK and international students) and stipend at UKRI rates p.a. (currently at £15,609). Funded by the University of Surrey's Department of Chemical and Process Engineering.

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