Pharmacometrics Lead AI​/Machine Learning

Make your mark for patients

We are looking for a Pharmacometrics Lead AI/Machine Learning who is innovative and agile to work in our Quantitative Clinical Pharmacology group
, based in our research site in Slough (UK),
Monheim (Germany) or Braine (Belgium).

Developing, implementing and leading Pharmacometrics AI/ML strategy to support development of our assets. Extrapolation (where appropriate), dose selection, trial design, PIP development and ongoing evaluation of data as generated.

Reporting to Global Head of Pharmacometrics.

• Evaluating and implementing emerging technologies for quantitative clinical pharmacology and pharmacometrics applications.
• Performing hands‑on AI/ML, population PK/PD, exposure-response modelling and clinical trial simulations on an assigned project.
• Developing submission‑ready, fit‑for‑purpose Pharmacometrics analysis plans and reports.
• Initiating and overseeing outsourced pharmacometrics and AI/ML activities and further internalising the work as needed.
• Supporting the development of a team from both a technical and scientific perspective to ensure state‑of‑the‑art pharmacometrics approaches are applied to optimise drug discovery and development.
• Having a working knowledge about the regulatory pathways on a global basis and opportunities for collaboration with health authorities (either through working parties, advice meetings and other initiatives) in Paediatrics, Neurology and Immunology.
• Working closely with the QCP Leads assigned to the various projects to ensure clear integration of the pharmacometrics aspects into the programmes.
• Promoting MID3 internally and externally.

• Doctorate (PhD or MD) in the related disciplines of pharmaceutical sciences, statistics or engineering.
• 8+ years (Bio) pharmaceutical industry experience in pharmacometrics with at least 2 years of experience in the applications of AI/ML in drug development.
• Hands‑on experience in population PK/PD, disease progression modelling and clinical trial simulations.
• Strong understanding and knowledge of Bayesian methodologies and model‑based meta‑analyses.
• Hands‑on expertise in R, Python, Matlab, NONMEM or related pharmacometrics software.
• Agile mindset with a proven ability to adjust by prioritising multiple tasks.
• Outstanding communication, organisational and presentation skills.

UCB is an equal opportunity employer. All employment decisions will be made without regard to any characteristic protected by applicable laws.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities, contact us on EMEA-Rea Please note that if your enquiry does not relate to adjustments, we will not be able to support you through this channel.