Connectionists: PhD position: Physics-based and Data-Driven Spectral Unmixing

[Ivan Ezhov]

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The lab for Artificial Intelligence in Medicine (AIM Lab<https://portal.mytum.de/jobs/wissenschaftler/NewsArticle_20240327_090905/www.aim-lab.io>) 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. The group focuses on pursuing blue-sky research, including:

  *   AI for medical imaging applications ranging from image reconstruction to analysis and interpretation
  *   AI for the early detection, prediction and diagnosis of diseases as well as for the identification of new biomarkers and targets for therapy
  *   Safe, robust and interpretable AI approaches as well as privacy-preserving AI approaches

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 the HyperProbe<https://hyperprobe.eu/> project aiming to develop a new optical imaging device that will provide real-time monitoring of cellular and molecular biomarkers. 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 and publications and previous experience with projects in these fields
  *   Extensive 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)

Notice for candidates with disabilities:

Candidates with disabilities will be given preference if they are essentially of the same suitability and qualifications.

How to apply:

Please send your application documents (CV, transcripts, and research statement) to ivan.ezhov at tum.de<mailto:ivan.ezhov at tum.de>

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