Building an engaging and intentional data culture and data literacy concept

Crack the code of data literacy and culture as part of our team. Data and information is the heart of our future and we want to crack the code together with you.

Developing profiling and segmentation algorithms to generate insights into our diagnostic customers’ needs

Roche is one of the major players in in-vitro diagnostics, with a plethora of assays, technologies and customers. We are curious to learn from your ideas: how could we profile and segment our customers to better understand their needs?

Identification of hidden patterns in diagnostics assay data

We believe that multi-biomarker panels have the potential to enhance the diagnosis, prognosis and monitoring of a broad range of diseases effectively. We are curious to learn from your ideas: how could we identify hidden patterns in our wealth of diagnostics assay data?

Interpretable ML models for automated quality assessment of measurement results

Machine Learning is gaining ground in the development of medical and diagnostic products. However, unfolding its full potential is hampered by lack of interpretability of “black box” models. So let’s build interpretable ML models for automated quality assessment of instrument results.

Machine-readable clinical practice guidelines in oncology

Artificial Intelligence (AI) is divided into probabilistic and logics-based approaches. Machine-readable clinical practice guidelines form a prime use case for bringing these two approaches together. Only combined AI approaches enable us to understand, explain, and trust the hints and paths provided by the system which ultimately leads to better outcomes for patients.

Greenfield Challenge

You have an idea to solve crucial healthcare questions through data know-how? You are looking for Roche as an industry partner to put your idea into practice? Then share it with us and we will come back to you if and how we can collaborate on your idea.