Internship - Bioprocess Data Science and Causal AI

The Position As the world leader in the production of innovative medicines, we at Boehringer Ingelheim offer you the opportunity to get to know the many tasks of digital Bioprocess Development. You will support us in developing Digital Twins for large-scale mammalian cell culture manufacturing, where we use time-course data from online sensors and offline metabolite measurements to predict process dynamics.Apply now for an internship in Biberach!As the world leader in the production of innovative medicines, we at Boehringer Ingelheim offer you the opportunity to get to know the many tasks of the Bioprocess & Analytical Development / Modelling and Data Analysis Division. You accompany us at pre-processing data and take responsibility for machine learning methods. Tasks & responsibilities

You will work on the following topic

Causal AI: Developing algorithms to distinguish between correlation and causation in bioreactor data to perform Root Cause Analysis on batch deviations.While this position is primarily intended as an internship, there may be a possibility to transition into a Master’s thesis project depending on project fit and internal opportunities.

Your Profile

Masterstudents in Bioinformatics, Bioprocess Engineering, Data Science, Statistics, or a related field Strong programming skills in Python (specifically Pandas, Scikit-Learn, and PyTorch) An understanding of cell metabolism or chemical engineering principles is a significant plus Analytical mindset with the ability to handle complex, high-dimensional datasets Good knowledge of MS Office Fluency in spoken and written English

What we can offer you

As a student intern, you can expect a fair expense allowance (payment of the currently valid minimum wage) You will be given 2.5 days of paid time off for every full month of the internship A full-time internship is 37.5 hours a week (a smaller number of hours can be arranged)

The duration of the internship is 6 months. The start can be made several times