Post Doc - Methods for Early Human Pharmacokinetic Prediction

The Position

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.

This Position is limited for 2 years.
Note: To make it easier to find our job advertisements, we use the usual designation "Post Doc". Of course, this advertisement is not only addressed to applicants directly after completing their doctorate, but to all qualified candidates.

Tasks & responsibilities

• In your new role you will develop and refine human PK prediction approaches at different stages of compound profiling from the design idea towards later stages of profiling, including different combinations of in-silico predictions, in-vitro ADME, and in-vivo PK data to enhance the reliability of early efficacious dose estimations. 
• You will evaluate and implement optimal PK prediction methods, including criteria for selecting the best approach based on available data and quantifications of uncertainties in PK predictions for transparent decision making. 
• Furthermore, you will 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. 
• You will contribute to the development and implementation of standardized guidelines for decision making based on early human dose prediction at different stages of compound profiling.
• Moreover, you will 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.
• In addition, you will actively share your results at internal and external meetings as part of the global postdoctoral community at Boehringer Ingelheim, present at scientific conferences and publish in peer-reviewed journals. Moreover, you will 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

Ready to contact us? 

If you have any questions about the job posting or process - please contact our HR Direct Team, Tel: +49 (0) 6132 77-3330 or via mail: hr.de@boehringer-ingelheim.com
 
Recruitment process:
Step 1: Online application - The job posting is presumably online until "January 04, 2026". We reserve the right to take the posting offline beforehand. Applications up to "December 22, 2025" are guaranteed to be considered.
Step 2: Virtual meeting in the period from mid-December till end of January
Step 3: On-site interviews beginning in January

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