Knowledge Transfer Partnership (KTP) Associate in Bioprocess Analytics and Machine Learning

This is an exciting opportunity for someone with a postgraduate/doctoral degree in a subject area of Bioprocess Engineering, Chemical Engineering, Biotechnology or a related field. The post holder will lead a cutting-edge innovation project in chemical engineering in a brand new way to the pharmaceuticals industry. Based at the GSK’s Stevenage Office, the KTP Associate will connect computational models to Raman spectroscopy systems for real-time data collection and ensure machine learning algorithms run efficiently for real-time bioreactor control. This will involve building an Automated Pipeline to Pre-Process and Integrate GSK’s Historical Data for initial Machine Learning Model Development, as well as developing machine learning models to predict critical process parameters and collecting additional experimental data and gaining hands-on experience with GSK’s bioreactor operations to enhance the accuracy and contextual understanding of machine learning models. Plus, the successful candidate will be part of the prestigious 50-year-old national Knowledge Transfer Partnership programme offering a dedicated professional development budget, a network of fellow Associates from many disciplines and training and mentoring opportunities. The Associate will also have the opportunity to write publications about their work alongside the academic and company team.

The KTP Associate is responsible for the day-to-day running of the project. The Associate will be expected to show initiative and independence of thought in applied research and embedding knowledge. They will also demonstrate inquisitive and project management skills in their industry-based role. Specifically, this includes:

1. developing an automated pipeline to pre-process and integrate GSK’s historical Process Analytical Technology (PAT)
2. developing machine learning models to predict critical process parameters
3. collecting additional experimental data and gaining hands-on experience with GSK’s bioreactor operations to enhance the accuracy and contextual understanding of machine learning models
4. integrating machine learning (ML) model predictions into bioreactor systems for real-time control, with an initial emphasis on glucose regulation.
5. scaling up the machine learning (ML)-enabled bioprocess control strategy to pilot and production scales.

In addition, the post holder will be expected to:

• Follow and promote UCL policies actively, including Equal Opportunities and Race Equality policies;
• Maintain an awareness and observation of fire and health and safety regulations;
• Carry out any other duties commensurate with the grade and purpose of the post.

The successful candidate will need to meet UCL’s expectations of core behaviours as outlined on the UCL website.

As duties and responsibilities change the job description will be reviewed and amended in consultation with the post holder.