Scientific Leader, AI-Driven Discovery & LIAL Systems

GlaxoSmithKline; Cambridge (MA); Hybrid; USD 158,000 - 263,000; Full time

Benefits offered by this job

Annual bonus

Health and other insurance

Retirement benefits

Paid holidays

Paid vacation

Parental/maternity leave

Job summary

GSK in Cambridge, MA is seeking a Scientific Leader in Discovery Integration Sciences to guide cross‑functional teams in designing, deploying and operating the System‑of‑LIAL‑Systems that power our research platform, combining computational intelligence with automated laboratory work.

You will turn scientific requirements into scalable system designs, mentor staff, and advance AI‑driven autonomous science in a fast‑moving biopharma environment.

Qualifications

• PhD or MS with computational science experience.
• 5+ years leading matrix teams across scientific and technical disciplines delivering software for wet/dry lab integration.
• 5+ years programming in Python and/or R.
• Experience with cloud tech to build data workflows and digital lab automation.
• Familiarity with Nextflow, Airflow or similar tools.

Responsibilities

• Collaboratively develop and deploy LIAL Systems with scientists and tech teams.
• Translate scientific requirements into system designs and enable platform capabilities.
• Lead cross-functional teams, mentoring others and fostering collaboration.
• Apply new methods and data sources to drive autonomous science using AI/Agents.
• Prepare presentations and reports for project teams and decision forums.

Skills

Python

R

Cloud platforms

Cross-functional leadership

AI and ML

Team mentoring

GIT / CI CD

Kubernetes

Education

PhD

MS + 3 years

Tools

Nextflow

Airflow

GCP

AWS

Azure

Kubernetes

Git/GitHub

CI/CD

Job description

GSK in Cambridge, MA is seeking a Scientific Leader in Discovery Integration Sciences to guide cross‑functional teams in designing, deploying and operating the System‑of‑LIAL‑Systems that power our research platform, combining computational intelligence with automated laboratory work.

You will turn scientific requirements into scalable system designs, mentor staff, and advance AI‑driven autonomous science in a fast‑moving biopharma environment.