PhD position on Deep Learning for Imaging Problems in the Machine Learning and Information Processing Group

03.11.2023, Wissenschaftliches Personal

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

The Machine Learning and Information Processing group at TUM works at the intersection of machine learning and signal/information processing with a current focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage.

We are seeking a researcher to join our team in a DFG funded project on deep learning for medical imaging. We are looking for a student with a strong mathematical and/or coding background. You must hold a master’s degree in Electrical Engineering, Computer Science, 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 we will not consider applications that are incomplete, generic, or not meaningful.

Please send your application or any questions on the position to: [email protected]
The position is open until filled.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

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Kontakt: [email protected]