The Position Join a global team that is shaping the future of datau2011driven 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 datau2011science expertise with scientific and business insights to enable smart, timely and confident decisionu2011making 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 with in the field of patientu2011specific clinical or realu2011world data and digital biomarkers. This position is part time eligible with 80%. Postdoc: This Position is limited for 2 years. 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 readyu2011tou2011use software, graphical user interfaces, technical reports, and scientific publications in close collaboration with statistics colleagues within and outside BI. You will also supervise bacheloru2019s and masteru2019s students on relevant subtopics, guiding them toward highu2011quality 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 peeru2011reviewed journals. Moreover, you will provide training on basic and advanced statistical learning methods to both statistics and nonu2011statistics colleagues across BI. Finally, you will collaborate closely with internal experts and play an integral role within the Statistics team, contributing to cuttingu2011edge 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 machineu2011learning techniques (e.g., penalized regression, support vector machines, treeu2011based methods) and advanced deepu2011learning methodologies Extensive experience in developing endu2011tou2011end machineu2011learning and deepu2011learning 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 datau2011science and deepu2011learning libraries such as NumPy, pandas, scikitu2011learn, Keras, TensorFlow, and PyTorch; knowledge of IT and highu2011performance 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) 6132 77-3330 or via mail: hr.de@boehringer-ingelheim.com (https://performancemanager5.successfactors.eu/xi/ui/rcmjobreq/pages/mailto%20hr.de@boehringer-ingelheim.com) Recruitment process: Step 1: Online application - The job posting is presumably online until March12th, 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 All qualified applicants will receive consideration for employment without regard to a personu2019s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.