All JobsResearch assistant / PhD position on Tissue Classification based on Machine Learning
The Chair for Computer Graphics at the University of Tübingen, headed by Prof. Dr. Hendrik Lensch, invites applications for a fully funded PhD position (TV-L E13, 100%) on Tissue Classification based on Machine Learning, as part of the interdisciplinary Research Training Group (RTG) 2543. The position is available immediately. It is limited to three years.
The aim of this project is to develop machine learning methods for heterogeneous, multimodal medical data, measured at individual points, as 2D gigapixel images or as 3D volumes. By fusing the information from different data modalities, the approach aims at supporting tissue classification before, during, and after the surgery.
Please find more information about the RTG2543 here: https://www.grk2543.uni-stuttgart.de/en/
Requirements:
- Excellent Master’s degree in computer science, engineering, or related disciplines (e.g., machine learning, mathematics, medical engineering, cognitive sciences)
- Background in medical image processing or machine learning
- Good programming skills in Python, C/C++
- Interest in interdisciplinary research
- Independent and committed workstyle
- Fluency in scientific English
Good to haves:
- Hands-on experience with ML frameworks (e.g., PyTorch, Tensorflow, Jax etc.)
We offer a flexible and interdisciplinary work environment in a motivated team that collaborates with well-known international institutes with possibilities of research visits, summer schools, and conference attendance.
The University of Tübingen strives for the implementation of equal opportunities and all qualified applications will be considered regardless of gender, color, origin, disability, sexual orientation etc. Please send your application as a single PDF file including a motivation letter, curriculum vitae, transcripts, certificates, and list of academic references (if any) to hendrik.lensch@uni-tuebingen.de. The hiring is done by the central administration.
The application deadline is January 20, 2023.
