Director, MIDD AI/ML Scientist

GSK

1d•Hybrid

About The Position

Director, MIDD AI/ML Scientist Clinical Pharmacology Quantitative Medicine (CPQM) is accountable for both applying clinical pharmacology strategies and the principles of quantitative medicine across RIIRU (Respiratory, Immunology & Inflammation Research Unit) to enable efficient, end-to-end development of transformative medicines. A key component of the CPQM mission is to harness the power of AI/ML & mechanistic modelling, to drive robust Development Strategies including Dose, Endpoint & Population Selection; Smart Clinical Trials and deliver Model Informed Drug Development (MIDD) evidence. Hybrid AIML-Pharmacometrics/QSP methodologies are a set of emerging approaches that combine the power and flexibility of AI/ML with the credibility of mechanistic modelling. This fusion has the potential to greatly enhance the predictive capabilities of CPQM by enabling the integration of novel data types (e.g. imaging, biomarkers, OMICs, digital endpoints, and real-world data) to drive more predictive and impactful insights for decision-making. Job Purpose The Director, MIDD AI/ML Scientist will focus on the practical application of emerging AI/ML and hybrid AI/ML-Pharmacometrics methodologies to projects on an asset and disease level supporting a wide range of clinical development decisions across RIIRU. The role will consist of collaborating with Clinical Pharmacology leads and cross-functional teams to integrate diverse sets of biomedical data (e.g. clinical, imaging, biomarkers, OMICs, digital health, or real-world data) into hybrid AI/ML-Pharmacometrics approaches. It will consist of direct stakeholder engagement, identification of impactful hybrid AI/ML modelling opportunities, analysis planning, execution, interpretation and communication of results and impact. This position is an excellent entry point for experienced quantitative scientists with a background in AI/ML (e.g. PhDs in AI/ML or related fields), drug development and Pharmacometrics/QSP looking to apply those techniques to benefit patients at the frontier of medicine. We create a place where people can grow, be their best, be safe, and feel welcome, valued and included. We offer a competitive salary, an annual bonus based on company performance, healthcare and wellbeing programmes, pension plan membership, and shares and savings programme. We embrace modern work practises; our Performance with Choice programme offers a hybrid working model, empowering you to find the optimal balance between remote and in-office work. Discover more about our company wide benefits and life at GSK on our webpage Life at GSK | GSK

Requirements

PhD (or equivalent) in AI/ML or related quantitative fields or in Life Sciences.
Strong foundation and experience in building and applying AI/ML models.
Strong foundation and experience in statistics and/or pharmacometrics / quantitative clinical pharmacology.
Strong industry drug development experience, working within teams.
Experience coding AI/ML pipelines in Python/Pytorch or Julia/Pumas.
Strong interest and experience in promoting hybrid AI/ML-pharmacometrics expertise.
Developing people and processes.
Excellent collaboration and communication skills (written, verbal and presentation), with experience working in interdisciplinary teams.

Nice To Haves

Direct pharmacometric project experience.
Direct experience applying AIML approaches for longitudinal data and/or SciML approaches.
Familiarity with the application of agentic AI to enhance novel process integration.

Responsibilities

Manage stakeholder engagement: Proactively interact with stakeholders, line and middle management, staff and external contacts on a functional and tactical level. Tactically identify high impact opportunities for hybrid AI/ML-pharmacometrics approaches on projects.
Execute portfolio projects: Apply AI/ML and hybrid AI/ML-pharmacometrics approaches to deliver analyses that inform drug development decisions (dose, regimen, endpoint, population, trial design).
Work cross-functionally: Collaborate with CPMS leads, QSP modellers, statisticians, and digital/imaging experts to integrate AI/ML analyses with existing modelling frameworks. This will cover developing analysis plans, conducting analyses and communicating interim/final results.
Contribute to our capabilities: Engage with academic groups and external vendors supporting joint internal-external projects and remaining abreast of cutting-edge methods. Identify best practices, trends, learnings, etc from internal and external sources and disseminate.
Drive awareness: Deliver training, seminars, and internal communications to increase literacy in AI/ML-pharmacometrics across CPQM and RIIRU.
Have external influence: Conference presentations, posters, and publications in scientific journals to represent GSK’s impact in AI/ML for drug development.