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Research Assistant/Associate in Electrode Modelling, Optimisation and Manufacturing

Newcastle University

Location: Newcastle upon Tyne, Work from home
Salary: £29,619 to £33,314 per annum.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 25th January 2023
Closes: 21st February 2023
Job Ref: 25000

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

The Role

Do you have a prior research background in machine learning, optimisation or modelling transport processes in fuel cells, electrolysers or batteries?

We are seeking to appoint an enthusiastic PDRA with experience in computational fluid dynamics, porous material modelling, machine learning algorithms and 3D printing. The project will involve the design and manufacture of novel 3D printed electrodes for electrochemical devices and is funded by the Connected Everything network, which aims to advance digital manufacturing tools. The candidate will be joining the electrochemical engineering group at Newcastle University and working closely with the PI to develop new models and algorithms for optimising fluid flow and transport in porous electrodes for fuel cells, electrolysers or batteries. The digital geometry designed will be manufactured working closely with 3D printing partner Photocentric.

The digital tools developed will be integrated into software (‘Porous Microstructure Generator') to enable knowledge transfer between industry. Opportunities to present work at conferences and host workshop on the project is encouraged.

This exciting project will provide the foundations for follow up research collaborations between the candidate and the PI.

As a Research Assistant/Associate, you will be a central member of the team, focusing on research, simulation, electrode design & manufacturing and integration of coded tools into the Porous Microstructure Generator tool.

Your main objective will be to develop a machine learning framework which can optimise a porous structure given constraints in the application of electrochemical devices.

The successful candidate will have extensive experience of academic research and collaborative projects. You will demonstrate your knowledge of the critical aspects of the interaction of porous electrodes with the performance of electrochemical devices.

You will be based at Newcastle University and due to the nature of the work, remote working will be possible if required. Visits to conferences and Photocentric may be required to present findings on research.

You should hold a PhD (or nearing completion) in mathematics, computer science, physical chemistry, chemical engineering, electrical engineering, or closely related disciplines. Additionally, evidence of continued professional development and industry experience is highly desirable.

We are committed to building and maintaining a fair and inclusive working environment and we would be happy to discuss arrangements for flexible and/or blended working.

The appointment is fixed-term, tenable for 5.25 months in the first instance until September 2023. The position is available on a full-time basis (37 hours per week).

For more information about the School of Engineering, and our research, please click here.

To apply, please complete an online application and upload a CV and cover letter. Your cover letter is a supporting statement, and you should outline how you meet the essential criteria of the role and evidence this with examples.

For informal queries regarding the role or the project, please contact Daniel Niblett, Research Associate in Mathematical Modelling, at: daniel.niblett@newcastle.ac.uk.

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