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Postdoc position in Strasbourg: DL, Domain Adaptation, Multi-Modal Representations

27 Novembre 2021

Catégorie : Post-doctorant

A Postdoc position is open at University of Strasbourg (ICube Laboratory) - France


Deep Learning, Domain Adaptation, Multi-Modal Representations

The position will be funded for two years (initially for one year, renewable for an additional year). The candidate will join the SDC research team under the supervision of Dr Thomas Lampert, the Chair of Data Science and Artificial Intelligence, and join his international team of PhD students and engineer to develop novel deep learning approaches to domain invariant representation learning (particularly in multi-modal data), with application (but not restricted) to Medical Imaging and Remote Sensing. The funding is not connected to a particular project, so it is the perfect opportunity for a strong candidate to explore new directions under the supervision of the Chair.


The successful candidate will have (or will soon obtain) a PhD in computer science or related domain and have experience in deep learning and applied machine learning and a strong level of written and spoken English. Experience with transformers, GANs, autoencoders, and/or unsupervised/self-supervised DL (autoencoders, etc) would be a plus. You will join a growing team and will have the freedom to follow your interests in a direction complementary to the abovementioned research focusses. You will be expected to target leading outlets in the field of machine learning and have a strong track record of publications. Candidates who are able to carry out the highest quality research independently, to co-supervise PhD students, and to give their input on a number of projects being carried out in the team are pursued. You will have access to state-of-the-art hardware for deep learning.

Send a letter of motivation, your CV, and an example publication to Thomas Lamper and Gisèle Burgart ( - !remove the numbers!) with the subject beginning with [Chaire Postdoc].


The position will remain open until a suitable candidate is found and the starting date will be agreed upon with the successful candidate (but can start ASAP).


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