Master Thesis Improving Model Evaluation in Applied

vor 5 Monaten

Bremen, Deutschland Digital Medicine Vollzeit

The Fraunhofer Institute for Digital Medicine MEVIS is a world-leading and internationally connected research center for computer assistance in medicine. With about 140 employees, our mission is to conduct patient-centric research and development to improve clinical processes for the benefit of our clinical partners and, in the end, patients.

**What you will do**

However, several methodological questions are still not solved to a satisfactory degree. For your Master thesis, you will work on one of four relevant topics to improve model evaluation in applied machine learning (planning of benchmark experiments, optimal data splitting, confidence intervals after cross-validation, modern evaluation strategies). For each topic, details on the goals, methods and work plan are available upon request.

**What you bring to the table**
- Enrolled student at a university
- Knowledge of statistical foundations
- Experience in R programming
- Interest in reproducible code and simulation studies
- English and/or German on a fluent level

**What you can expect**
- A friendly and interdisciplinary working environment close to the University of Bremen
- Self-determinded work and the freedom to develop the thesis topic
- A steady supervision concept fitting your needs
- Ideal conditions for practical experience alongside your studies

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

For questions regarding this positions, do not hesitate to contact

Dr. Max Westphal

Fraunhofer Institute for Digital Medicine MEVIS

Requisition Number: 70038 Application Deadline:

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