Research Fellow in Digital Tw

Profile

Research Fellow in Digital Twin of Electrochemical Decarbonisation
University of Surrey
- Chemical & Process Engineering
Location:
Guildford
Salary:
£35,308 to £38,474 per annum
Hours:
Full Time
Contract Type:
Fixed-Term/Contract
Placed On:
12th June 2023
Closes:
30th June 2023
Job Ref:
028323
Post Type: 
Full Time, Fixed Term
Closing Date: 
23.59 hours BST on Friday 30 June 2023
Reference: 
028323
Applications are invited for a Research Fellow in Developing Digital Twin for the Electrochemical Carbon Dioxide Reduction Processes as part of the EPSRC-funded project on the Digital Circular Electrochemical Economy (DECC) which aims to address the decarbonisation of the chemical sector through use of non-fossil feedstocks and integration of electrified processes into the wider renewable energy sector. We take an integrated techno-economic, sociotechnical and political approach to apply digital technologies to transform the environmental sustainability of the chemical sector, the 3rd-higest industrial (direct) emitter of CO2
The post will be based within the School of Chemistry and Chemical Engineering (SCCE) at **MEMBERS ONLY**SIGN UP NOW***., and will have opportunity to interact with a vibrant DCEE research team from the other 3 universisties (Imperial College London, Loughborough and Heriot-Watt) and a number of industrial partners.
About the project
In this project, we will develop a digital twin framework for the key electrochemical processes to enable the proposed circular electrochemical economy. This will serve as a real-time predictive/decision making tool to self-optimise unit operations in response to the high uncertainties of energy and feedstock supplies, and exchange information with the higher-level digital value chain frameworks encompassing the integration between chemical and electrical systems.
The Research Fellow will be part of a large DCEE consortium, aiming to accelerate the transition of the chemical industry to net zero carbon through circular approaches and electrification of processes. The Research Fellow is expected to collaborate closely with partners on the DCEE project to integrate the process-scale models into broad system framework for a whole system optimisation.
This position is initially for a duration of 12 months with a very high possibility for further extension for at least the other 12 months. The preferred start date would be on the 1st August 2023.
About you
We are looking for a highly motivated researcher with solid research experience in data-driven modelling to develop a digital twin for electrochemical CO2
conversion electrolysers, with particular skills in machine learning (ML) and artificial intelligence (AI). You will be expected to conduct ML and AI-based simulation and decision-making based optimisation of the electrolysers based on open-source platforms, e.g., Python and Matlab. You must possess a solid understanding of data-driven methodologies and exhibit proficiency in coding and programming, along with a firm grasp of the basics of electrochemical processes. Previous experience using advanced optimisation techniques, and applying physics-informed ML and AI methodoliges will be an advantage.
All candidates must hold (or be close to completion of) a PhD in Chemical Engineering, Mechanical Engineering, Physics, Computer Science or other relevant major degrees. Prior experience in programming is essential, preferably in Matlab and/or Python.
How to apply
Candidates should apply via our website, carefully answering all the application form questions, and attaching a CV (with details on education, research experiences, successes, and the relevant publications to date). As part of the application, you should also upload two letters of recommendation as the supporting documents.
Prospective applicants can contact Prof. Jin Xuan ( ****
) or Dr. Lei Xing  ( ****
) if they need any specific further information on the post.
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