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.
This project is hosted at the Biomedical Image Analysis and Machine Learning Lab of the University of Zurich. More/additional information can be found here. The project can also be carried out remotely.
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.
In this Master thesis, we aim to develop novel semi-offline reinforcement learning (RL) methods for the task of active feature acquisition (AFA) and apply these methods to the medical problem of sepsis diagnosis.
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.
We currently have no vacancies for PhDs or Post-Docs
Unfortunately we cannot host any external students for internships.