Internship - Bioprocess Data Science and Causal AI

Boehringer Ingelheim GmbH; Biberach an der Riß; Vor Ort; EUR 16.000 - 21.000; Vollzeit

Benefits dieser Stelle

Fair expense allowance

2.5 days paid time off per full month

37.5 hours per week internship

Zusammenfassung

Boehringer Ingelheim GmbH in Germany invites a Master student to join the Bioprocess Data Science and Causal AI internship, supporting the development of Digital Twins for large-scale mammalian cell culture manufacturing and using time-course sensor data to predict process dynamics.

You will assist in pre-processing data, apply machine learning methods, and work within the Bioprocess & Analytical Development / Modelling and Data Analysis Division.

Qualifikationen

• Master students in Bioinformatics, Bioprocess Engineering, Data Science, Statistics or related field.
• Strong programming skills in Python and ML libraries.
• Fluent English, able to handle large datasets.

Aufgaben

• Pre-process data and develop Digital Twins for mammalian cell culture.
• Develop Causal AI algorithms to distinguish correlation from causation.
• Support modelling and data analysis within the division.

Kenntnisse

Python

Pandas

Scikit-Learn

PyTorch

MS Office

Ausbildung

Master student

Jobbeschreibung

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.

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

• Masterstudentsin 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 a year. The earliest possible start date is November 1, 2026.