AI-Driven Assay Scientist: Data & Workflows

RMT Labs; Basel; On-site; CHF 120,000 - 180,000; Full time

Job summary

Roche Basel seeks a highly versatile Scientist to bridge wet-lab science with advanced digital infrastructure. You will design closed-loop analytical systems, build data-driven workflows, and champion platform adoption across the department to enable rapid, reproducible science. You hold a Ph.D.

or M.S. in a quantitative biology discipline and bring strong programming skills, LIMS/ELN experience, and DoE know-how to deliver FAIR, Findable and interoperable data assets from complex assays.

Qualifications

• Ph.D. or MS in quantitative biology with computational focus.
• Experience with cellular/biochemical/biophysical systems and FAIR data.
• Experience with laboratory informatics environments (LIMS/ELN) and DoE.
• Strong programming skills: databases, automation, ML/LLM API integration.

Responsibilities

• Lead co-development and rollout of end-to-end LIMS and data trails.
• Design and integrate Agentic AI tools and DoE frameworks.
• Build pipelines linking instrument outputs to databases for FAIR data.
• Coordinate onboarding and training for bench scientists and stakeholders.
• Accelerate assay design and execution times, reduce bottlenecks.

Skills

Computational biology

Data engineering

LIMS experience

DoE frameworks

ML/LLM API integration

Stakeholder training

Education

Ph.D. in Computational Biology or related field

M.S. in Computational Biology or related field

Tools

LIMS

Electronic Lab Notebooks (ELN)

Database management

Automation scripting

Job description

Roche Basel seeks a highly versatile Scientist to bridge wet-lab science with advanced digital infrastructure. You will design closed-loop analytical systems, build data-driven workflows, and champion platform adoption across the department to enable rapid, reproducible science. You hold a Ph.D.

or M.S. in a quantitative biology discipline and bring strong programming skills, LIMS/ELN experience, and DoE know-how to deliver FAIR, Findable and interoperable data assets from complex assays.