PhD position in the Machine Learning and Information Processing Group on DNA Data Storage

Updated: about 2 years ago
Deadline: The position may have been removed or expired!

28.01.2022, Wissenschaftliches Personal

The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%, 3 years) on DNA data storage.

The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a 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 collaborative project on DNA data storage. The project focuses on developing information theory, coding schemes, and other algorithms, including ones based on machine learning for DNA data storage and DNA information processing in general. Here is a video on the topic:
https://www.bbc.com/future/article/20151122-this-is-how-to-store-human-knowledge-for-eternity
We are looking for a student with a strong mathematical and/or coding background. Interest and ideally a background in coding theory, information theory, algorithms, and or machine learning is desired. You must hold a master’s degree in Electrical Engineering, Computer Science, Mathematics, Physics, or a similarly quantitative field. The work is interdisciplinary and we will closely collaborate with a group at the chemistry department at ETH Zurich.

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 definitely 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 can start any time, the early the better, and will remain open until filled.

We offer an interesting, challenging, and interdisciplinary academic environment, a supportive research team, and excellent working conditions at the research facility of TUM. TUM is aiming to increase the number of women employees, and applications from women are expressly welcomed. Preference will be given to candidates with disabilities with essentially the same qualifications.

Data Protection Information:
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Kontakt: [email protected]



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