Post-Doc in Modeling Multi-modal Medical Data
The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data.
The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is located at Klinikum Rechts der Isar, the university hospital of TUM, in the institute of radiology. We are affiliated with the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We are looking for a Post-Doc (TVL E13) to join our team.
Medical images provide wide opportunities for studying diseases. Yet, images alone are often not sufficient but the integration of adjunct data sources is required to create a holistic picture. Such additional information can improve the performance, help to reveal biases, or may enable to perform causal inference. We are interested in developing statistical models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice.
Qualifications
- PhD in (Bio-)Statistics, (Bio-)Informatics, Computer Science or related disciplines
- Strong background in modeling multi-modal data (images, tables, text, etc)
- Understanding of biases and causal inference
- Experience with machine and deep learning
- Programming experience with Python and Pytorch
- Strong analytical and problem-solving skills
- Excellent communication & interdisciplinary skills
- Fluency in English (written and spoken)
Location
The hospital is located in the city center of Munich near the river Isar. Munich is a vibrant technology hub with many cultural and recreational offerings, including the nearby Alps.
Application
Please send your application documents (CV, transcripts, cover letter) to [email protected]. The position can start as early as 1. January 2023.
Die Stelle ist für die Besetzung mit schwerbehinderten Menschen geeignet. Schwerbehinderte Bewerberinnen und Bewerber werden bei ansonsten im wesentlichen gleicher Eignung, Befähigung und fachlicher Leistung bevorzugt eingestellt.