Post Doc AI & Machine Learning for R&D

As a Postdoctoral Scientist in Generative AI for Chemistry and Analytical Sciences at Boehringer Ingelheim, you will help shape digital research capabilities that support scientific discovery in chemical R&D. Based at our global headquarters in Ingelheim, Germany, you will bring together chemistry, analytics, data science, and digital innovation to develop AI and machine learning solutions for real research challenges. Your work will improve how scientific data is analyzed, how knowledge is accessed, and how digital workflows support researchers in their daily work. In close collaboration with colleagues across science, data, digital product teams, and R&D sites, you will turn emerging AI technologies into reliable, practical, and user-centered solutions. This Position is limited for 2 years. 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. Tasks & responsibilities

• One of your key responsibilities will be to develop and implement AI-supported methods, particularly generative AI and machine learning, to analyze and utilize reaction data within the AURORA program.
• In regard to model development, you will train AI models using our in-house reaction data database to identify relevant historical data and generate practical suggestions for new chemical or analytical questions.
• Moreover, you will extract, structure, and prepare unstructured datasets to make scientific information searchable and ready for use in AI applications.
• In addition, you will validate AI-generated suggestions in close collaboration with chemists and analysts from Research and Development to ensure scientific relevance and practical applicability.
• Furthermore, you will support the operational integration of the developed AI solutions into Boehringer Ingelheim’s existing AI infrastructure, working closely with IT and data science teams.
• You will document the methods, models, and results developed and present progress clearly within interdisciplinary project teams.

• A completed PhD in Data Science, Computational Science, Computer Science, Chemistry or Analytics.
• Proven experience in generative AI and/or machine learning (e.g. through publications, projects or comparable evidence).
• Basic IT skills for the practical, operational implementation of AI models within existing infrastructures.
• Business-level proficiency in spoken and written English.
• Initial applied experience in industry, ideally relating to chemical or analytical problems.
• Experience in handling unstructured datasets, as well as an interest in the interdisciplinary interface between chemistry/analytics and data science.

As part of our commitment to transparency and fairness, salary information will be shared during the recruitment process. We also offer a comprehensive benefits and wellbeing package.