PhD Positions on Foundation Models and Deep Learning for Imaging Problems

Technical University of Munich Department of Computer Engineering

PhD positions on Foundation Models and Deep Learning for Imaging Problems

19.04.2024, Wissenschaftliches Personal

The Professorship of Machine Learning at the Department of Computer Engineering at TUM has open positions for a doctoral researcher (TV-L E13 100%, 3-4 years) on Foundation Models and/or Deep Learning for Imaging Problems.

The Professorship for Machine Learning at TUM works on machine learning, artificial intelligence, and information processing. The current focus is on developing algorithms and foundations for deep learning and foundation models, particularly for medical imaging and on establishing mathematical and empirical underpinnings for machine learning.

We are seeking a researcher to join our team in an DFG funded project on deep learning for medical imaging and/or for a project on foundation models.

We are looking for a student with a strong mathematical and/or coding background. You must hold a master’s degree in Computer Science, Electrical and Computer Engineering, Mathematics, or similar. Knowledge in machine learning is desired. We are looking for a driven person with the desire to do high-quality research.

TUM is ranked consistently as one of the best universities in Europe and often as the best technical university in Germany, an excellent place to do a PhD. Our group is part of the School of Computation, Information and Technology. We are working with groups in the US and Europe, and offer opportunities to collaborate internationally with a variety of researchers.

We offer a fully paid position (TV-L E13 100%) and interesting research project in a diverse team with the opportunity to do a PhD.

Your application should comprise at least: An application letter pointing out why you are interested in our work and a detailed curriculum vitae together with transcripts of grades. We do not expect overly formal application material, but will not consider applications that are incomplete, generic, or not meaningful. Please send your application or any questions on the position to: The position is open until filled.

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