Post Doc - Methods for Early Human Pharmacokinetic Prediction

Post Doc - Methods for Early Human Pharmacokinetic Prediction

Shape the future of drug discovery as a Postdoctoral Researcher in the Preclinical PK/PD Modeling and Data and Digital Sciences team within the global Drug Discovery Sciences department. In this role, you will advance early human pharmacokinetic (PK) prediction by developing prediction approaches that integrate in‑silico, in‑vitro, and in‑vivo data across species at various stages of compound profiling, enabling continuous ranking and targeted optimization of new drug candidates. Collaborate with an interdisciplinary team of experts in drug discovery to deliver impactful solutions that enable data‑driven decision making and accelerate the progression of promising drug candidates. This work will directly support our mission to identify high‑quality first‑in‑class drug candidates and make significant contributions to breakthrough therapeutic concepts.

Tasks & Responsibilities

• Develop and refine human PK prediction approaches throughout compound profiling, integrating in‑silico predictions, in‑vitro ADME, and in‑vivo PK data to enhance the reliability of early efficacious dose estimations.
• Evaluate and implement optimal PK prediction methods, selecting the best approach based on available data and quantifying uncertainties in PK predictions for transparent decision making.
• Integrate project‑specific information and systematically assess the timing and availability of data throughout the test cascade to optimize prediction methods at each stage, supporting compound prioritization and progression.
• Contribute to the development and implementation of standardized guidelines for decision making based on early human dose prediction at different stages of compound profiling.
• Collaborate closely with internal and external interdisciplinary teams of experts from PK/PD modeling, in‑vitro ADME, computational chemistry, data science, and machine learning, combining multiple data sources and advancing machine‑learning in‑silico PK predictions.
• Actively share results at internal and external meetings, present at scientific conferences, and publish in peer‑reviewed journals. Gain insights into drug discovery strategies in the pharmaceutical industry with opportunities for further career development.

Requirements

• PhD in a field related to pharmacometrics. The PhD should either be already obtained or the defense of the PhD thesis is already foreseeable.
• Basic knowledge in biology, DMPK and/or pharmacology.
• Proven skills in PK, PK/PD, PBPK and/or longitudinal disease modelling.
• Proficiency in (statistical) programming languages and pharmacometric tools e.g., R, MATLAB, Phoenix WinNonLin, NONMEM.
• Authentic, enthusiastic, cooperative, and creative personality with good communication skills in English.

Recruitment Process

Step 1: Online application – Applications up to December 22, 2025 are guaranteed to be considered.

Step 2: Virtual meeting – Mid‑December to end of January.

Step 3: On‑site interviews – Beginning of February.

Contact

Questions about the job posting or process – please contact our HR Direct Team:
Tel: +49 (0) ‑3330
Email:

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