Senior Scientist

Senior Scientist

Lonza

Cambridge, United Kingdom

Based in Cambridge, this role offers the opportunity to work hands-on in the lab while helping shape next-generation mammalian expression platforms. As a Senior Scientist, you will play a key role in developing innovative CHO expression systems that enable faster and more efficient production of complex therapeutic proteins.

What you will do

• Act as a core contributor or wet lab lead on key projects focused on mammalian cell expression systems, spending approximately 80% of your time in hands-on laboratory work
• Contribute to the development and delivery of new CHO-based mammalian expression hosts for the production of complex therapeutic proteins
• Engineer mammalian cell lines using random integration, targeted integration and CRISPR-based gene editing approaches
• Design and generate mammalian expression vectors using state-of-the-art DNA assembly techniques
• Perform phenotypic characterisation of edited cell lines using methods such as NGS, ddPCR, qPCR, flow cytometry and advanced cell culture techniques
• Analyse, interpret and sign off experimental data, ensuring high-quality outputs and fully traceable records
• Present results through clear written reports and oral presentations to internal stakeholders
• Mentor and support junior scientists, fostering technical development and knowledge sharing within the team
• Collaborate closely with cross-functional teams to deliver robust and scalable expression solutions

What we are looking for

• A PhD or MSc with relevant experience in an R&D environment
• Strong technical expertise in CHO cell line engineering and development
• Experience in molecular biology techniques used to develop and manipulate mammalian expression systems
• Demonstrated contributions to technology development projects, including experience transferring new technologies into GMP manufacturing environments
• Strong collaboration skills and a proactive, solutions-focused mindset
• Working knowledge of experimental design and applied statistics