Scientific Leader, Discovery Integration Sciences

GSK; Upper Providence (Delaware County); On-site; USD 121,000 - 175,000; Full time

Job summary

GSK in Stevenage seeks a Scientific Leader for Discovery Integration Sciences to shape and deliver the System-of-LIAL-Systems powering its research platform. You will lead cross-functional teams of scientists and engineers, translate complex scientific requirements into scalable software, and advance autonomous science using AI and data-driven methods.

This role offers exposure to cutting-edge biopharma discovery, collaboration across R&D and tech, and opportunities to influence the future of

Qualifications

• PhD or equivalent with computational emphasis.
• 5+ years leading matrix scientific/technical teams in software-enabled discovery.
• 5+ years programming in Python and/or R.
• Experience with modern software tools (Git, CI/CD) and cloud tech.

Responsibilities

• Collaboratively design and deploy LIAL Systems with scientists and tech teams.
• Translate scientific needs into scalable platform capabilities.
• Lead cross-functional teams and mentor others.
• Apply new methods/tools to accelerate autonomous science using AI/Agents.
• Produce clear presentations for project governance.

Skills

Python

R

Cloud technologies

CI/CD

Git/GitHub

Nextflow

Airflow

Kubernetes

Leadership

Cross-functional collaboration

Education

Doctoral degree in a relevant scientific discipline

MS +3 years professional experience in a relevant scientific discipline

Tools

Git

GitHub

Nextflow

Airflow

Kubernetes

Job description

Business Introduction

At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people's lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients' needs and have the highest probability of success. We’re uniting science, technology, and talent to get ahead of disease together.

Find out more

Our approach to R&D

Description

For UK candidates seeking to be located at our Stevenage site, this role will temporarily be based at Stevenage. However, the Company plans to relocate its offices to Cambridge and Ware. The location of this role will therefore subsequently change to Cambridge or Ware in accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029.

Job Title: Scientific Leader, Discovery Integration Sciences

Job Purpose

Do you share a desire to advance scientific knowledge and capitalise on the revolution in data, automation and predictive sciences to deliver measurable impacts on the success and progression of GSK's medicine discovery portfolio?

The Data, Automation and Predictive Sciences (DAPS) function of GSK Research Technologies focuses on large-scale data generation, curation, analysis and prediction to deliver higher PTRS (Probability of Technical and Regulatory Success) assets and unlock upper quartile ambitions. Within DAPS, the Discovery Integration Sciences team is driving efforts across Research to build the world's most efficient and effective biopharma discovery platform at GSK by building and deploying innovative Lab-in-a-... etc. Each LIAL System will deliver a domain leading scientific discovery solution that leverages and extends state-of-the-art scientific methods by engineering technologies to create integrated discovery systems that empower GSK research scientists with the latest tools. LIAL Systems will therefore be physical instantiations of GSK's mission to unite science, technology and talent to get ahead of disease together.

As a Scientific Leader in the Discovery Integration Sciences team you will work and lead across scientific and technical disciplines in cross-functional teams designing, delivering and operating the System-of-LIAL-Systems that will power GSK's Research activities and the underlying LIAL Platform that provides the abstracted blueprint and technical services for building and operating LIAL Systems at scale.

Key Responsibilities

• Collaboratively and iteratively develop and deploy LIAL Systems by partnering with scientists and technical teams across R&D and Tech to (re)design experimental processes for LIAL enablement and implement as integrated systems.
• Translate scientific requirements into system designs and enabling platform capabilities and conversely articulate platform capabilities as system enablers of improvements to scientific processes.
• Foster inclusive high-quality scientific and technical collaboration by working within and leading cross-functional matrix teams which mentoring and supporting others.
• Introduce and apply new methods, tools, and data sources to drive innovation and continuously improve the speed, quality, and predictability of autonomous science using AI and Agents.
• Prepare clear presentations and reports for project teams and decision-making forums.

Basic Qualifications

• Doctoral degree (PhD or equivalent) or MS +3 years professional experience in a relevant scientific discipline with a significant computational component.
• Minimum of 5 years professional experience working in and leading matrix teams across scientific and technical disciplines to deliver software projects integrating wet lab and dry lab capabilities in a continuously evolving landscape.
• Minimum of 5 years of experience programming and software engineering using Python (preferred) and/or R.
• Experience with modern software development tools / ways of working (e.g. object-oriented programming, git/GitHub, CI/CD).
• Minimum of 3 years of experience using cloud technologies (e.g. GCP, AWS, Azure, Kubernetes) to build and deploy data workflow automation (e.g. Nextflow, Airflow), digital lab automation (e.g. orchestration, scheduling) and/or integrated ("lab-in-the-loop") solutions.

Preferred Qualifications

• Proven track record of designing, developing and deploying complex scientific software solutions with clear impact.
• Strong leadership skills demonstrated by leading projects, influencing decisions and communicating with multidisciplinary teams and senior stakeholders in a cross-functio