Research Associate/Fellow in Optimisation for 3D Printing

Economics Network; Nottingham; Hybrid; GBP 32,000 - 47,000; Full time

Job summary

Economics Network at the University of Nottingham invites applications for an 18-month full-time research role developing software tools for biocatalytic flow reactors. You will build and advance the computational framework to enable design optimisation and propose more efficient designs.

The role requires a PhD in engineering, physics or related, and proven ability with Python or Matlab. Knowledge of 3D printing is desirable.

Qualifications

• PhD required in engineering, physics or related discipline.
• Proven ability to use Python or Matlab.
• Knowledge of 3D printing desirable.

Responsibilities

• Develop and advance the computational framework for biocatalytic flow reactors.
• Enable design optimisation and propose new, more efficient designs.
• Contribute to publications and present research at conferences.

Skills

Python

Matlab

3D printing

Education

PhD in Engineering, Physics or related discipline

Job description

This post is part of the EPSRC Programme Grant “Dialling Up Performance for On Demand Manufacturing". This project aims to develop a TOOLKIT to enable the rapid formulation of 3D printable materials into products. This toolkit will be composed of an integrated suite of software and experimental tools and will be informed by the collection of data en route to the development of advanced 3D printed products. The focus of this specific role is the development of software tools that support the development of TOOLKIT: to develop and use optimisation techniques to determine new geometrical configurations suitable for a range of products. Initially this will be aimed at biocatalytic flow reactors, but it is anticipated that other applications may be considered. This is an interdisciplinary collaboration that will require working with researchers across engineering, catalysis, optimisation and computational modelling.

Your role will be to develop and advance the computational framework describing biocatalytic flow reactors to enable design optimisation to be performed, and new, more efficient designs to be proposed and manufactured. You will aid in writing publications, present research at national and international conferences and liaise with collaborators. You will be given support to develop and shape your future career, and hence this position may be particularly attractive to those looking to develop their research independence and leadership skills in a supportive and team-oriented environment.

You must have (or about to complete) a PhD in engineering, physics or a related discipline. A demonstrable ability to use scientific languages and packages, such as Python or Matlab, is essential and a knowledge of 3D printing and related techniques is desirable. You will have good interpersonal skills and the ability of working in a team to tight deadlines. The CV and/or cover letter should clearly exemplify how you meet the criteria highlighted herein and in the Role Profile and describe your motivation for applying for this position.

The post is for a period of 18 months and is based in the Faculty of Engineering at the University of Nottingham. The position is available from 1st November 2026, or as soon as possible thereafter. This is a full time (36.25 hours/week) position, but flexible working times and a small amount of home working are possible to support those with specific requirements. We value diversity and are committed to equality of opportunity, and we welcome applications from all sections of the community.

Further details:

We are proud to be a Disability Confident Employer (Level 2) employer. Increasing the diversity of our community is extremely important to us and we are committed to the aims of Disability Confident Scheme.

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Your application will be considered on an equal basis, subject to the relevant permission to work in the UK as set out by UK Visas & Immigration.

£32,080 to £47,389 per annum, depending on skills and experience (minimum £35608 with relevant PhD).