Pharmacometrics Lead AI/Machine Learning - UK, Belgium or Germany

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).

About the role

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.

Who you’ll work with

Reporting to Global Head of Pharmacometrics. 

 

What you’ll do

Evaluating and implementing emerging technologies for quantitative clinical pharmacology and pharmacometrics applications.

Performing hands-on AI/ML, population PK/PD, exposure-response modeling 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 internalizing 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 optimize 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 programs.

Promoting MID3 internally and externally.

Interested?  For this role you'll need the following education, experience and skills

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 modeling, 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 prioritizing multiple tasks.

Outstanding communication, organizational and presentation skills.

Internal applicants should be in their current job for at least 12 months, must meet performance standards and are not on formal corrective/disciplinary process (PIP), warning, final warning, or compliance warning letters within the last 12 months. Please inform your Manager or your Talent Partner before applying to any internal job opportunities.

At UCB, we’ve embraced a hybrid-first approach to work, bringing teams together in local hubs to foster collaborative curiosity. Unless expressly stated in the description, this role is hybrid with 40% of your time spent in the office, irrespective of your current contractual agreement. Should your current working arrangements differ, please contact your Talent Partner to discuss, before submitting your application.

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-Reasonable_Accommodation@ucb.com . Please note should your enquiry not relate to adjustments; we will not be able to support you through this channel.

 

Requisition ID: 92247

Recruiter: Joanna Coombs

Hiring Manager: Akash Khandelwal

Talent Partner: Geraldine Beauduin

Job Level: SM II

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