At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

Job facts

Do you have a passion for healthcare and an interest in digital wearables? Are you eager to gain experience in clinical research and data analysis? If so, we have the perfect internship opportunity for you!

As an intern in NPC assay formats (Near Patient Care RED Chapter- NPC RED), you will have the opportunity to be a part of an innovative, and a global team. The NPC RED Chapter is located in Mannheim and develops innovative diagnostic solutions for near-patient testing. We work together with departments from Research & Development, Diagnostics Production, Business Development and the Life Cycle Teams.

Your tasks

• Screening of patents, literature, and clinical studies relevant to the project.

• Conduct analysis of the data from wearables using complex regression frameworks.

• Providing regular updates to cross-functional team of clinical scientists, biomarker experts, data scientists, and IVD experts.

Who You Are

We are looking for a candidate who is inspired by our mission and thrives in a collaborative, high-tech environment. To be successful in this role, you possess:

• Academic Background: Currently enrolled in a Master’s program in Computer Science, Data Science, Physics, or Engineering, with a heavy emphasis on Machine Learning.

• Sensor Domain Expertise: A deep technical understanding of how digital wearables detect, filter, and transmit physiological metrics.

• Time-Series Proficiency: Hands-on experience handling large, time-stamped datasets. You excel at transforming noisy, raw sensor data into high-quality features for regression analysis.

• Technical Stack: Proficient in Python or R for predictive modeling. Experience with scikit-learn and XGBoost.

• Scientific Rigor: Meticulous attention to detail in writing technical reports, and documentation.

• Communication Skills: Fluent in English.

Your benefits

• Flexible working hours (37.5 hours/week)

• Attractive recognition grant (2,268 Euro per month for a full-time internship > 3 months)

• Discounted meal prices (- 50%) in our staff canteen

• Sport Center on campus

• Online/Offline student networking events

Your application

Along with your CV/resume, please provide a cover letter (maximum 350 words) describing your suitability for the position.
Please remember that this thesis internship is aimed at students (m/f/d) who are currently enrolled for the entire period of the internship.