Research Fellow in Digital Chemistry and Engineering

University of Leeds; Leeds; On-site; GBP 30,000 - 42,000; Full time

Job summary

A leading UK research university is seeking a Research Fellow in Digital Chemistry and Engineering to advance sustainability in pharmaceutical manufacturing through innovative automation and data-driven optimisation. You will integrate self-optimising flow reactor technology with high-throughput experimentation and industry collaboration. This role offers opportunities for flexible working and various employee benefits, including extensive holiday and gym memberships.

Benefits

26 days holiday plus 16 Bank Holidays

Discounted gym membership at The Edge

Access to personal development courses

On-site childcare and shopping discounts

Qualifications

• PhD or equivalent experience in a relevant area.
• Experience with machine learning applications.
• Strong interest in sustainable practices in chemical engineering.

Responsibilities

• Advance sustainability of pharmaceutical manufacturing.
• Upgrade self-optimising flow reactor platform.
• Collaborate with industry partners on case studies.

Skills

Machine learning expertise

Data-driven optimisation

Sustainability metrics

High-throughput experimentation

Analytical science

Education

PhD in relevant field

Job description

Research Fellow in Digital Chemistry and Engineering

Are you an experienced and ambitious researcher looking for your next challenge? Do you want to further your career in one of the UK’s leading research-intensive Universities? Are you eager to apply your machine learning expertise to cutting-edge automated optimisation challenges?

We are seeking a Research Fellow in Digital Chemistry and Engineering to combine self-optimising flow reactor technology with high-throughput experimentation (HTE) and apply it to pharmaceutically relevant case studies.

The overarching goal of the project is to advance the sustainability of pharmaceutical manufacturing through innovative automation, analytical science, and data-driven optimisation. You will upgrade a self-optimising flow reactor modular platform integrated with high-throughput experimentation (HTE) and online process analytical technology (PAT), embedding sustainability metrics into the optimisation loop, and apply transfer learning to accelerate the transition from batch to continuous flow processes. You will interact with project partners in the pharmaceutical sector to demonstrate the technology on high impact case studies.

This project is part of a £10M+ project funded by innovate UK and will involve extensive collaboration with industry partners including AstraZeneca, Labman and Britest.

The position will be based at the Institute of Process Research and Development, in the School of Chemistry, University of Leeds.

We are open to discussing flexible working arrangements.

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

Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information, please visit the Government’s Skilled Worker visa page.

• 26 days holiday plus approx.16 Bank Holidays/days that the University is closed by custom (including Christmas) – That’s 42 days a year!
• Health and Wellbeing: Discounted staff membership options at The Edge, our state-of-the-art Campus gym, with a pool, sauna, climbing wall, cycle circuit, and sports halls.
• Personal Development: Access to courses run by our Organisational Development & Professional Learning team.
• Access to on-site childcare, shopping discounts and travel schemes are also available.