Research Associate in Digital-Twin of Fischer-Tropsch Reactors (DigiTwin-FT)

University of Sheffield; Sheffield; On-site; GBP 35,000 - 48,000; Full time

Job summary

The University of Sheffield's DigiTwin-FT project seeks a Research Associate to develop a predictive digital twin for scaling up CO₂-to-fuel Fischer-Tropsch reactors. You will work with pilot facilities and real data to validate high-fidelity models and contribute to sustainable chemical manufacturing.

Collaborating with industry partner Siemens, you will address scale-up challenges and greenhouse-gas emissions while benefiting from full training if CO₂ utilisation knowledge is desired but not

Qualifications

• Chemical process engineering background required.
• Strong process modelling or digital twin experience essential.
• Knowledge of CO₂ utilisation desirable but not essential; full training provided.

Responsibilities

• Develop a predictive digital twin for Fischer-Tropsch reactors.
• Utilise pilot-scale facilities and real operational data to validate the model.
• Collaborate with industry partner Siemens on cutting-edge research addressing scale-up and emissions.

Skills

Process modelling

Digital twin

Education

Chemical process engineering background

Job description

Research Associate in Digital-Twin of Fischer-Tropsch Reactors (DigiTwin-FT)

Be part of DigiTwin-FT, a pioneering Great British Chemicals-funded project at the University of Sheffield, working to accelerate the UK’s transition to sustainable, circular chemical manufacturing.

Working alongside Professor Mo Zandi and Dr James McGregor, you’ll help develop a predictive digital twin for scaling up CO₂-to-fuel Fischer-Tropsch (FT) reactors. Using Sheffield’s pilot-scale facilities, you’ll work with real operational data to validate a high-fidelity digital model capable of simulating thermo-kinetic behaviour at commercial scale.

In collaboration with industry partner Siemens, you’ll contribute to cutting-edge research addressing greenhouse-gas emissions, scale-up challenges and the development of value-added chemicals from waste carbon.

We’re looking for someone with a chemical process engineering background and strong process modelling or digital twin experience. Knowledge of CO₂ utilisation is desirable but not essential-full training will be provided.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.