Postdoc TAM (Machine Learning)

The Position

Join a global team that is shaping the future of data‑driven clinical development. Biostatistics and Data Sciences (BDS) is a worldwide organization within the Human Pharma Business Unit. In close collaboration with internal functions and external partners, we combine deep methodological and technical data‑science expertise with scientific and business insights to enable smart, timely and confident decision‑making across all stages of drug development, approval and patient access.

As we continue transforming BDS into a modern data science organization capable of thriving in a rapidly evolving environment, we are expanding our capabilities to fully unlock the value of our clinical data. To support this journey, we are seeking a Postdoctoral Researcher who will advance innovative Machine Learning methodologies within the field of patient‑specific clinical or real‑world data and digital biomarkers. This position is part‑time eligible with 80% effort. The position is limited to a 2‑year period. Note: To make it easier to find our job advertisements, we use the usual designation "postdoc". Of course, this advertisement is not only addressed to applicants directly after completing their doctorate, but to all qualified candidates.

Ready to shape the next generation of clinical data science? Apply now and join us on this exciting journey.

Tasks & responsibilities

• In your new role you will identify, implement, and evaluate innovative methods in areas such as multivariate statistical prediction models, supervised and unsupervised learning, model assessment and explainable AI, optimized feature engineering, and deep learning approaches for signal processing and computer vision
• In addition, you will translate your research into ready‑to‑use software, graphical user interfaces, technical reports, and scientific publications in close collaboration with statistics colleagues within and outside BI
• You will also supervise bachelor’s and master’s students on relevant subtopics, guiding them toward high‑quality internship reports, theses, and associated software outputs
• Furthermore, you will actively build and maintain networks with academic institutions to foster collaboration and exchange of expertise
• You will present your findings at internal and external meetings and contribute to the scientific community through publications in peer‑reviewed journals
• Moreover, you will provide training on basic and advanced statistical learning methods to both statistics and non‑statistics colleagues across BI
• Finally, you will collaborate closely with internal experts and play an integral role within the Statistics team, contributing to cutting‑edge data science initiatives across the organization

Requirements

• PhD in Mathematics, Statistics, or a related quantitative field, supported by a strong scientific foundation
• Proven expertise in both classical machine‑learning techniques (e.g., penalized regression, support vector machines, tree‑based methods) and advanced deep‑learning methodologies
• Extensive experience in developing end‑to‑end machine‑learning and deep‑learning pipelines, from data preparation to model deployment
• Knowledge of generative modeling or Large Language Models, as well as familiarity with clinical development processes, is considered an advantage
• Strong proficiency in R, ideally including experience with R Shiny, R Markdown, Quarto, and the development or publication of R packages
• Solid programming skills in Python, including the use of core data‑science and deep‑learning libraries such as NumPy, pandas, scikit‑learn, Keras, TensorFlow, and PyTorch; knowledge of IT and high‑performance computing is an advantage
• Demonstrated track record of publishing scientific work, along with fluency in written and spoken English and strong interpersonal skills for effective collaboration with internal and external stakeholders

Ready to contact us?

If you have any questions about the job posting or process - please contact our HR Direct Team, Tel: +49 (0) or via mail:

Recruitment process

Step 1: Online application - The job posting is presumably online until March 12th, 2026.

Step 2: Virtual meeting end of February / beginning of March 2026.

Step 3: In-depth interviews beginning of end of March/beginning of April 2026. Please include the following documents when applying for this position: CV & application letter.

Why Boehringer Ingelheim?

With us, you can develop your own path in a company with a culture that knows our differences are our strengths - and break new ground in the drive to make millions of lives better. Here, your development is our priority. Supporting you to build a career as part of a workplace that is independent, authentic and bold, while tackling challenging work in a respectful and friendly environment where everyone is valued and welcomed. Alongside, you have access to programs and groups that ensure your health and wellbeing are looked after - as we make major investments to drive global accessibility to healthcare. By being part of a team that is constantly innovating, you’ll be helping to transform lives for generations. Want to learn more? Visit