Research Associate in Bioprocess Modelling and Optimisation

The University of Manchester; Manchester; Hybrid; GBP 30,000 - 40,000; Full time

Job summary

A leading educational institution in Manchester is seeking a Postdoctoral Research Associate to advance innovative algae-based carbon capture technology. The role involves developing models, optimising processes, and working collaboratively with industry partners. Candidates should have a PhD or be nearly complete in a relevant field, with skills in process modelling and machine learning. This position offers excellent benefits including a market-leading pension scheme and emphasis on equality and diversity.

Benefits

Market leading Pension scheme

Employee health and wellbeing services

Exceptional annual leave entitlement

Paid closure during Christmas

Local and national discounts

Qualifications

• Candidates should hold or be nearing completion of a PhD.
• Experience in algal bioprocess modelling and optimisation is desirable.
• Prior experience with machine learning and data-driven modelling is a plus.

Responsibilities

• Develop, evaluate, and optimise the ACCU process.
• Work closely with project partners on digital twin modelling.
• Contribute to joint publications and participate in meetings.

Skills

Dynamic process modelling

Bioprocess optimisation

Machine learning

Data-driven modelling

Algal biotechnology

Education

PhD in chemical/biochemical engineering or related discipline

Tools

Process simulation software

Modelling software

Job description

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.

Overall Purpose of the Job

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.

What you will get in return:

• Fantastic market leading Pension scheme
• Excellent employee health and wellbeing services including an Employee Assistance Programme
• Exceptional starting annual leave entitlement, plus bank holidays
• Additional paid closure over the Christmas period
• Local and national discounts at a range of major retailers

The School/Department is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School/Department holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. All appointment will be made on merit. For further information, please visit: http://www.ceas.manchester.ac.uk/about-us/athena-swan/

Our University is positive about flexible working - you can find out more here

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to [e-mail] . Any CV's submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr Dongda Zhang

Email: [e-mail]

General enquiries:

Email: [e-mail]

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.