Research Associate in Waste-to-Microbial Protein Research

About us

This role will be located at Department of Engineering, King College London Strand Campus.

Recently re-founded, the Department of Engineering is rapidly expanding into a world-class research and teaching department. Research currently focuses on robotics, telecommunications and biomedical engineering, but we are looking to establish new research themes.

We offer both undergraduate and postgraduate teaching, with a distinctive approach, combining both traditional teaching methods with modern, project-based learning, catering for the needs of our students and the industries in which they will work.

As a new department we have invested in new laboratories and maker space at the centre of the Strand campus in the heart of central London.

For more information: https://www.kcl.ac.uk/engineering

About the role

This post holder will join a cross-disciplinary research project ‘TRANSFORM ‘Waste—to-Microbial-Protein’ funded by Good Food Institute (GFI). The project will harness the advancement in computational modelling and develop new tools and knowledge on optimised, scalable and sustainable mycoprotein fermentation based on low-cost, food-grade alternative carbon sourced from lignocellulosic polysaccharides and retailer liquid waste. By combining experiments and modelling research, the project will map out the global food-grade sustainable carbon from crop residues and contribute new knowledge on the selected fungal strain growth in response to varying carbon sources.

The project will develop a software to automate data processing, machine learning model selection and optimisation and enable end-users to design and optimise microbial protein solutions with minimal user intervention. The position holder will have the opportunity to work together with industry partners to engage wider stakeholders in academic-industry co-creation and advance the understanding of the feasibility and sustainability of the protein fermentation.

The key responsibilities of the post holder include:

• Develop machine learning models to map out the resource potential of sustainable sugar-rich waste streams (e.g. lignocellulosic polysaccharides and retailer waste).
• To collaborate with team members and develop mechanistic models to simulate microbial synthesis to produce protein from complex sugar sources.
• To develop a simulation-optimisation tool to automate data-handling, model construction and optimisation and inform microbial protein technology scale-up.
• To efficiently plan and manage own research activities and collaborate with others; write up research work for publications.
• To collaborate with wider academic and industrial partners on knowledge transfer activities.
• Attend and contribute to internal research meetings and project meetings.
• To present the research in conferences and industrial-focused workshops and events.
• To communicate research effectively with wider audience.

This is a full time post (35 Hours per week), offered on an 18-months fixed term contract.

About you

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

1. Knowledge in machine learning and mathematical optimization
2. Understanding of fermentation process
3. Proficient in programming in OOP (object oriented programming) environment
4. Excellent skills in communication and presentation
5. Capability in independent research
6. Capability in collaboration in dynamic and cross-disciplinary environment
7. Highly motivated and enthusiastic to deliver research within timeline
8. PhD qualified in relevant subject area (or pending results)

Desirable criteria

1. PhD in Chemical Engineering
2. Research experiences in process systems engineering
3. Academic writing skills and experience in research proposal development
4. Understanding of analytical experiments

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, via the above ‘Apply’ button.

Closing date: 14 July 2024

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