Job Description

We are seeking to recruit a Research Associate (RA) to work under the supervision of Dr. Dongda Zhang at the Department of Chemical Engineering, The University of Manchester. This project aims to develop state-of-the-art digital technologies for the UK Anaerobic Digestion (AD) industry to effectively improve process performance and achieve the ambitious net-zero target. The project combines the use of advanced techniques from machine learning, data-driven modelling, and process system engineering. This project is in collaboration with multidisciplinary research teams at the University of Surrey, the University of Southampton and the University of Nottingham.

The main purpose of the role is to develop AI-enabled digital twin for AD process real-time predictive modelling and optimisation. Candidates should already hold or be nearing completion of a PhD in chemical/biochemical engineering or process systems engineering, with focus on dynamic modelling/optimisation or machine learning/data-driven modelling. The candidate is expected to present results periodically to the other group members, and project partners, attend progress meetings and actively engage with other team\'s members. Previous experiences on bioprocess dynamic modelling, chemical/biochemical reaction kinetic modelling, multi-objective optimisation, data-driven and hybrid modelling are desirable and particularly welcome.

The School/Department is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School/Department holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. All appointment will be made on merit. For further information, please visit: http://www.ceas.manchester.ac.uk/about-us/athena-swan/.

Our University is positive about flexible working - you can find out more

Blended working arrangements may be considered

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dongda Zhang

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General enquiries:

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This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.

University of Manchester