The Lab for AI in Medicine at TU Munich develops algorithms and models to improve medicine for patients and healthcare professionals.
Our aim is to develop artificial intelligence (AI) and machine learning (ML) techniques for the analysis and interpretation of biomedical data. The group focuses on pursuing blue-sky research, including:
We have particularly strong interest in the application of imaging and computing technology to improve the understanding brain development (in-utero and ex-utero), 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.
Hyperspectral imaging (HSI) is an optical technique that processes the electromagnetic spectrum at a multitude of monochromatic, adjacent frequency bands. The wide-bandwidth spectral signature of a target object’s reflectance allows fingerprinting its physical, biochemical, and physiological properties.
In this course students are given the chance to apply their abilities and knowledge in deep learning to real-world medical data. Students will be assigned a medical dataset and in close consultation with medical doctors create a project plan.
Description In an era where technology has seamlessly integrated with our day-to-day lives, health and fitness tracking has seen a revolutionary change. Gone are the days when we passively absorbed health information.
In this Master thesis we aim to approach the cross-domain transfer learning problem with two powerful methods that help us to bridge the domain gap between source and target domain: contrastive learning [1] and generative models.
Anonymizing data means removing or replacing any identifying information from a dataset, such as names or addresses. The aim of anonymization is to protect the privacy of individuals whose data is being collected and processed.
We are recruiting team members who would like to join us for a MSc, BSc or guided research/interdisciplinary project on an ongoing basis! Please look under Teaching to find out which projects we are currently offering. If you’d like to join us for one of these projects, please get in touch by contacting the appropriate staff member via e-mail and attach a motivation letter, transcript of academic records and CV.
PhD position: Physics-based and AI-Driven Spectral Imaging for Brain Surgery
We are currently recruiting a PhD student to work on an EIC Pathfinder Project (HyperProbe). The project aims to develop a new hyperspectral 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
How to apply
Please send your application documents (CV, transcripts, and a brief motivation) to ivan.ezhov@tum.de.
Notice for candidates with disabilities
Candidates with disabilities will be given preference if they are essentially of the same suitability and qualifications.
Unfortunately we cannot host any external students for internships.