Research Fellow in Precision Manufacturing

University of Leeds
Leeds, West Yorkshire
Grade 7 (£33,797 - £40,322 p.a.)
Closing date
28 Sep 2021

Job Details

School of Chemical and Process Engineering and the School of Chemistry,

Faculty of Engineering and Physical Sciences.

Salary: Grade 7 (£33,797 - £40,322 p.a.) Due to funding restrictions, an appointment will not be made higher than £34,804 p.a.

Reference: EPSPE1048

Tenure: Fixed term for 3 years

Closing date: Tuesday 28 September 2021

We will consider job share and flexible working arrangements

Are you looking to apply your skills in automation for the development of new approaches for manufacturing nanoscale products? Do you want to further your career in one of the UKs leading research-intensive Universities?

We are seeking a Research Fellow in Precision Manufacturing to join a major 3-year EPSRC-funded programme - NanoMan: Self-Optimising Nanoscale Manufacturing Platforms for Achieving Multiscale Precision.

In this project we will build platform technologies, comprising advanced chemical reactors underpinned by computational intelligence, which can scale up production of advanced nanoparticle products (polymer nanoparticles and quantum dots) without loss in the precise control over structural dimensions which are achieved in research laboratories. You will build laboratory reactors which can be programmed to monitor the nanoparticle formation process in real time and relate conditions to the particle properties. You will incorporate and optimise machine learning algorithms which will direct the reactors towards achieving the desired specification through 'self-optimisation' of conditions. We will take the optimised laboratory nanoparticle formation processes and demonstrate scale in several manufacturing environments, including R&D process laboratories and manufacturing facilities at our partner’s sites.

Your position will be based at the School of Chemical and Process Engineering and the Institute of Process Research and Development at Leeds. You will interact with partners at AstraZeneca, DeepMatter and Somaserve to develop automated reactor platforms for nanoscale particle generation and work with collaborators at the University of Sheffield in the integration of machine learning algorithms. You will also undertake a secondment to one or more of our partner sites to demonstrate the processes on industrially relevant reactor platforms.

You will have a PhD (or close to completion) in Chemical Engineering, Chemistry or a closely allied discipline with experience in automated systems and their control, together with a demonstrable record of the ability to solve process and equipment problems, and generate new process understanding.

How to apply

To view the job description and to apply online, please visit our website.

Contact Information

To explore the post further or for any queries you may have, please contact:

Nicholas Warren, Associate Professor in Polymer Engineering (Project Lead)

Tel: +44 (0)113 343 4609



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