Senior Bioprocessing Scientist

About the role

The Senior Bioprocessing Scientist will lead the translation of manual 2‑D cell culture processes into closed, automated bioprocesses for ATMP manufacturing. Working within the CGT Catapult Scale Enabling Technology (SET) team, you will collaborate across sites to drive upstream process development, automation and digitalisation, reducing manufacturing costs and strengthening supply chains.

Key responsibilities

• Provide subject‑matter expertise in bioprocessing of autologous and allogeneic ATMPs, including viral vector platforms.
• Design, execute and document laboratory experiments, ensuring data integrity and compliance with biosafety and COSHH regulations.
• Lead integration of automation, PAT and digital tools across upstream processes, working with data, analytical and IT teams.
• Manage resources, budgets and timelines in collaboration with project sponsors and Lead Scientists.
• Present findings at internal and external meetings, and contribute to scientific conferences.
• Mentor junior scientists and provide line‑management where required.

Required profile

• Significant experience in a commercial biotechnology, biopharmaceutical or advanced therapy environment.
• Hands‑on expertise with upstream bioreactor systems (stirred‑tank, DASbox, BioBLU, ambr250, Quantum Flex, univessel).
• Proven track record in PSC cell bioprocessing, 2‑D/3‑D culture, cell thawing, expansion, differentiation and banking.
• Experience delivering training, conducting GMO risk assessments and managing health‑and‑safety compliance.
• Ability to work independently on complex research projects with minimal supervision.

Required skills

• Stirred‑tank bioreactors and automated cell culture platforms (DASbox, BioBLU, ambr250, Quantum Flex, univessel).
• Flow cytometry, qPCR, metabolite profiling and cell counting assays.
• Bioprocess data structuring, analysis and reporting (ELN, data integrity standards).
• Process analytical technology (PAT) integration and digitalisation.
• Design of Experiments (DoE) and statistical analysis for robust experimental design.