Internship - Data and Digital Enablement (PRLABD)

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

Internship in Machine Learning for Analytical Signal Data

Our Data and Digital Enablement department is part of Large Molecule Research (LMR) within Roche’s Pharma Research and Early Development (pRED) organisation in Penzberg.

We develop, implement and operate data-driven software and AI solutions for Process Research & Analytics, including the processing and automated analysis of process and analytical data.

Your internship

You will develop and evaluate machine-learning and deep-learning methods for large datasets of analytical signals, including time series, spectra and multidimensional measurements.

Your work will focus on information extraction, representation learning and automated analysis, ranging from benchmarking new approaches to developing robust, usable ML tools.

You will take ownership of well-defined projects, supported by your supervisor and scientists from different disciplines.

You will also learn how the underlying measurements are generated and used in pharmaceutical research.

What matters to us

Teamwork: You enjoy exchanging ideas, are open to feedback and contribute your own perspective.

You value learning from colleagues while being willing to question established approaches.

Courage: You take ownership of your work and approach technical and scientific challenges with curiosity.

You work independently and try new approaches when the obvious solution does not work.

Continuous learning: You are motivated to develop your skills, work in a structured and persistent way, and use setbacks to deepen your understanding and improve your approach.

 

Your profile


* This internship is open to students enrolled at a higher education institution throughout the internship.

Applicants in a gap year between their Bachelor’s and Master’s degrees are also eligible with written university confirmation that enrollment will resume within the 12-month gap year.


* You are preferably at an advanced stage of your studies in a quantitative or computational discipline.

Other academic backgrounds are welcome with relevant technical experience.


* You have hands-on experience implementing and evaluating ML approaches in Python, whether through coursework, research, internships or personal projects.

You are comfortable setting up your own development environment, using Git and managing dependencies.


* Deep learning experience is a strong advantage.

Additional experience with signal processing, scientific computing, software engineering, Linux, ...