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PhD position: Physics-based and AI-Driven Spectral Imaging for Brain Surgery

02.06.2024, Wissenschaftliches Personal

A PhD position within an EIC Pathfinder Project (HyperProbe) focusing on the development of spectral unmixing approaches for identifying biomarkers of brain activity.

The lab for Artificial Intelligence in Medicine (AIM Lab) focuses on AI and ML approaches for medicine and healthcare. Our aim is to develop AI and ML techniques for the analysis and interpretation of biomedical data. We have a particularly strong interest in the application of imaging and computing technology to improve the understanding of brain development, to improve the diagnosis and stratification of patients with dementia, stroke and traumatic brain injury as well as for the comprehensive diagnosis and management of patients with cardiovascular disease and cancer.

We are based in the Faculty of Medicine at the Campus Klinikum Rechts der Isar (which is the university hospital of TUM) as well as in the Faculty of Informatics at the Campus Garching. Our lab is affiliated with several machine learning initiatives in Munich, including the Munich Center for Machine Learning (MCML), the European Laboratory for Learning and Intelligent Systems (ELLIS Munich) and the Munich Data Science Institute (MDSI).

We are currently recruiting a PhD student to work on an EIC Pathfinder project (HyperProbe). The project aims to develop a new optical imaging instrumentation providing real-time monitoring of brain activity for patients diagnosed with glioma. The student will work on computational aspects of the project, designing physics- and data-driven algorithmic solutions for the reconstruction and analysis of hyperspectral data.

Qualifications:

  • An MSc in Computational Sciences, Physics, or related disciplines
  • Programming experience with Python and ML frameworks (e.g. Pytorch)
  • Strong analytical and problem-solving skills
  • Excellent communication & interdisciplinary skills
  • Fluency in English (written and spoken)
How to apply:

Please send your application documents (CV, transcripts, and a brief motivation) to ivan.ezhov@tum.de.

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Kontakt: ivan.ezhov@tum.de