BACKGROUND

We are seeking to recruit a Postdoctoral Research Associate (PDRA) to work under the supervision of Dr. Dongda Zhang at the Department of Chemical Engineering, the University of Manchester. This project aims to advance and demonstrate the industrial feasibility of an innovative two-stage algae-based carbon capture and utilisation (ACCU) technology, with the goal of derisking scale-up and enabling commercial deployment. The work will integrate model based design of experiments, machine learning, hybrid and kinetic modelling (digital twin development), process design, simulation and optimisation, and business case analysis, tailored to real-world industrial partner sites. The project will be delivered in close collaboration with Loughborough University, Heriot-Watt University, and three industrial partners from different sectors, providing a unique opportunity to address carbon emissions from small- to medium-scale emitters while generating high-value products and co-benefits such as wastewater treatment and biogas upgrading.

The main purpose of the role is to develop, evaluate, and optimise the innovative two-stage algae-based carbon capture and utilisation (ACCU) process, working closely with project partners to integrate experimental results, digital twin modelling, process optimisation, and whole-system analysis into industrially relevant solutions. The PDRA will contribute to model based design of experiments, algal bioprocess modelling and optimisation, machine learning and data-driven modelling, and business case development, ensuring the technology is optimised for deployment across diverse industrial sites. Candidates should already hold or be nearing completion of a PhD in chemical/biochemical engineering, process systems engineering, environmental engineering, or a related discipline, with expertise in dynamic process modelling, bioprocess optimisation, or machine learning/data-driven/hybrid modelling. The candidate is expected to engage actively with academic and industrial collaborators, present results regularly to project partners, participate in progress meetings, and contribute to joint publications. Prior experience in algal biotechnology, bioprocess modelling and optimisation, or machine learning and data-driven modelling is desirable and particularly welcome.