TU Dresden
A joint project with Uni Leipzig DE EN

AI in Oncology

Mentored by Sayan Mukherjee, Jakob Nikolas Kather
at Leipzig University, in close exchange with the MPI for Mathematics in the Sciences

We consider two related topics: clinically actionable predictions in oncology based on AI methods; and the biases and economic impact of AI in the clinic. The two groups involved Kather and Mukherjee offer complimentary expertise for cutting edge research in the use of AI for clinical predictions. Kather is a physician/scientist and has extensive experience in using and developing AI tools for clinical applications, he also brings the perspective of the clinician to the problem. Mukherjee has extensive experience in the use of statistics, machine learning, and AI for clinical applications, he brings the perspective of a methods developer and theoretician. We will focus on developing and using existing AI methods prediction of cancer outcomes as well as examining the economic impacts and biases of how AI may be used in the clinic.

Work Environment

You will have access to the machine-learning HPC resources of the ScaDS.AI Center for Scalable Data Analytics and AI Dresden/Leipzig, offering state-of-the-art CPU (Intel and IBM POWER 9) and GPU (Nvidia A100 and V100) resources, as well as high-performance computing and storage systems for computational experiments.

Prerequisites

The candidates can come from either a biomedical/clinical background or a quantitative science background. Previous experience in coding and analyzing data is a must.