(Senior) Scientist, Protein Engineering

About the role

The China Innovation Center of Roche (CICoR) in Shanghai is looking for a Scientist or Senior Scientist to discover, design and engineer novel antibody drugs. The final position offered depends on the candidate's experience. The role involves engineering antibodies through rational design, computational engineering or display technologies, working with dynamic teams and collaborating with colleagues in Biologics Discovery and Development, Immunology, Oncology, Cardiovascular and Metabolic Disease Discovery, Protein Sciences, Structural Biology, AI Data and Digital, Pharmaceutical Sciences and Biologics CMC.

Key responsibilities

• Contribute as a project member or BDD project lead, collaborating with cross-functional project leads on program strategy and goals.
• Perform protein engineering to drive therapeutic antibody lead selection, design and optimization.
• Design and execute display libraries (phage, yeast or in vitro display) for antibody optimization.
• Design and select antibody formats suitable for the project.
• Develop and apply computational and AI/ML tools for protein engineering and antibody optimization.
• Coordinate with CROs and monitor outsourcing to ensure timely delivery of qualified data.
• Take part in due diligence to evaluate external opportunities for licensing in assets or technologies.

Required profile

• Ph.D. in Protein Engineering, Biophysics, Structural Biology, Computational Biology or a related discipline.
• At least 3 years of post-doctoral or industry experience, preferably in biotechnology or pharma.
• Track record of supporting antibody generation and optimization in drug discovery programs.
• Publications and a history of consistent research productivity.

Required skills

• Sequence and structure-based protein analysis and engineering.
• Antibody humanization, affinity maturation, developability optimization and display technologies.
• Bi- and multi-specific antibody formats.
• Computational protein engineering, paratope-epitope modeling, immunogenicity reduction and NGS.
• Integrating AI/ML models (structure/sequence prediction) into wet-lab workflows.
• Cloning, site-directed mutagenesis, library construction and cell-based assays (binding, signaling, cytotoxicity) are a strong plus.