• Aberdeen University Featured PhD Programmes
  • Cardiff University Featured PhD Programmes
  • University of Birmingham Featured PhD Programmes
  • Castelldefels School of Social Sciences Featured PhD Programmes
  • University of East Anglia Featured PhD Programmes
  • University of Glasgow Featured PhD Programmes
  • University of Cambridge Featured PhD Programmes
University of Pennsylvania Featured PhD Programmes
Imperial College London Featured PhD Programmes
John Innes Centre Featured PhD Programmes
Coventry University Featured PhD Programmes
European Molecular Biology Laboratory (Heidelberg) Featured PhD Programmes

Model-reduction based optimisation and model predictive control for multi-scale chemical and biochemical systems

Project Description

Ph.D. studentships are currently available for research on optimization and model predictive control methodologies for multi-scale systems. The project will place a particular focus on microscopic/stochastic systems with applications in industrial biotechnology and predictive microbiology. The project builds on the group’s years of experience on model reduction methodologies for optimisation and control of systems described by large sets of nonlinear partial differential equations and of multi-scale systems dynamically coupling macroscopic and micro/mesoscopic simulations.

See http://www.manchester.ac.uk/research/k.theodoropoulos/publications for a list of our relevant publications.

There are funding opportunities available based on the academic track-record of applicants, and evidence of research potential.
Competition for funds is expected to be extremely high.

Research will be supervised by Prof. Theodoropoulos and involves the development of novel algorithms based on model reduction techniques for systems ranging from the microscopic (molecular/atomic level) to the mesoscopic scale.

Candidates should ideally have an MSc and a 1st class BSc in Chemical Engineering or a related field such as Physics, Applied Mathematics, Physical Chemistry etc. and should have computational modelling experience and good knowledge of a programming language (FORTRAN and/or C/C++).
Successful candidates will be enrolled in the 3-year Ph.D. program of the School of Chemical Engineering and Analytical Science.

Funding Notes

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Applications for this project are welcome from suitably qualified candidates worldwide.


1. Bonis, I, Xie, W & Theodoropoulos, C 2014, 'Multiple model predictive control of dissipative PDE systems' IEEE Transactions on Control Systems Technology, vol 22, no. 3, 6566038, pp. 1206-1214. DOI: 10.1109/TCST.2013.2270182.

2. Bonis, I, Xie, W & Theodoropoulos, C 2012, 'A linear model predictive control algorithm for nonlinear large-scale distributed parameter systems' AIChE Journal, vol 58, no. 3, pp. 801-811. DOI: 10.1002/aic.12626.

3. Theodoropoulos, C 2011, Optimisation and linear control of large scale nonlinear systems: A review and a suite of model reduction-based techniques. in Lecture Notes in Computational Science and Engineering|Lect. Notes Comput. Sci. Eng.. vol. 75, Lecture Notes in Computational Science and Engineering, vol. 75, Springer Verlag, Berlin-Heidelberg, pp. 37-61, International Research Workshop: Coping with Complexity: Model Reduction and Data Analysis, Ambleside, 1 July. DOI: 10.1007/978-3-642-14941-2_3

Related Subjects

How good is research at University of Manchester in Aeronautical, Mechanical, Chemical and Manufacturing Engineering?
Chemical Engineering

FTE Category A staff submitted: 33.90

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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

Cookie Policy    X