Digital Twin Research Associate: CO2-to-Fuel FT Reactors

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

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