Lead Pharmacometrician AI / ML

A Global Biopharmaceutical company who specialise in the development of therapies for neurological and autoimmune diseases are growing their Pharmacometrics team. This growth is dcaused by the need to meet the increasing volume of clinical trials. Along with their drive to continue to improve their capabilities as a Group as they continue to remain at the cutting edge of the sector.

There are seeking an agile and forward thinking Lead Pharmacometrician who has expeirnece with AI / Machine Learning to join their Pharmacometrics team.

The Key Responsibilities are:

• Performing AI / ML, population PK / PD, exposure response modeling and clincial trial simulations for your assigned projects.
• Assess and then implement new technologies for pharmacometrics and quantitative clinical pharmacology applications.
• Responsible for the management of outsourced pharmacometrics and AI/ML activities and internalise where necessary.
• Develop fit for purpose and submismission ready Pharmacometrics analysis plans & reports.
• As a senior member of the team you will support the development of team from a technical & scientific perspective. With the purpose to ensure state of the art mechanistic approaches are used to optimise drug discovery & development.
• Have a working knowledge of regulatory pathways on a global basis to seek opportunities for collaboration with health authorities in relevant disease areas.

As a Lead Pharmacometrician you will report directly to the Global Head and work closely with QCP leads. This is a very visible position which influences the integration of pharmacometrics aspects of the programmes.

For this position you will need to have:

• PhD or MD in Pharmaceutical Sciences, Statistics, or related area.
• Experience in the field of Pharmacometrics.
• Demonstrable experience of AI / ML applications in the field of drug develop and discovery.
• Experience in disease progression and PK/PD modeling and clinical trial simulations.
• Understanding of Bayesian methodlogies and model based meta analyses.
• Experience in the use of R, Python, Matlab and NONMEM for example.
• Strong communication skills and working in a fast paced & dynamic environment.