Research Fellow in Techno-Economic Modelling for Sustainable Protein Production

Are you an ambitious researcher looking for your next challenge? Do you have an established background in techno-economic modelling in food or bioprocesses? Do you want to play a leading role in developing an AI platform to valorise agri-food waste-streams and improve protein security?

We are looking for a Research Fellow in Techno-Economic Modelling for Sustainable Protein Production to join our international and interdisciplinary team developing an open-source AI platform for microbial protein from agri-food waste-streams, which has recently been awarded £2M from the Bezos Earth Fund as part of their AI for Nature and Climate Grand Challenge.

Nearly 29% of the world’s population faces food insecurity, yet millions of tonnes of nutrient-rich agri-food waste is generated globally each day. This waste can be upcycled into sustainable, high-quality microbial protein (e.g. yeast, fungi, bacteria and algae) via fermentation for use as ingredients in existing foods or to produce novel meat and dairy alternatives. However, microbial fermentation processes are difficult to design, optimise and scale up, especially for complex, and highly variable waste streams. This limits their investment attractiveness and economic viability, especially for small and medium enterprises (SMEs), and ultimately their global adoption.  

The University of Leeds in collaboration with the Commonwealth Science and Innovation Research Organisation (Commonwealth Scientific and Industrial Research Organisation, Australian Government - CSIRO) in Australia will develop the world’s first open-access AI platform to address these challenges by streamlining the development of microbial protein production processes. Leveraging advances in modern AI, the platform will consist of a Waste to Protein AI Engine coupled with an adaptive user interface enabling users to input their waste composition, volume, and location and immediately receive actionable insights, such as optimised fermentation parameters, microbial strain recommendations, projected protein yields and economic returns. Our AI platform will also provide users with an R&D roadmap that recommends critical trials to perform during process development and scale-up to reduce experimentation needs and provide partnership recommendations for areas where they lack expertise, facilities or market access. 

You will be based in the Food AI Lab (www.foodailab.co.uk) in the School of Food Science and Nutrition and benefit from engaging with the growing AI, Alternative Protein and Food activities at the University of Leeds including the National Alternative Protein Innovation Centre (National Alternative Protein Innovation Centre (NAPIC) - NAPIC) the Leeds Institute for Data Analytics Food Community (LIDA: Food | Leeds Institute for Data Analytics) and the Global Food and Environmental Institute (Global Food and Environment Institute | University of Leeds). You will also benefit from collaborating with CSIRO and numerous industry partners in the UK and across the globe.

You will have a PhD (or near to completion) in Engineering, Food Science, Computer Science or a closely allied discipline; a background in techno-economic modelling and research experience in food or bioprocess design. You will have a proven ability to work well both individually and, in a team, including partners from other countries, disciplines and industry. 

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

Professor Nik Watson 

Email: n.j.watson@leeds.ac.uk

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