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to the HEXAPIC project Carry out research in the predefined areas Disseminate results in top scientific venues Providing guidance to PhD and MSc students Participating in proposal writing Participating in teaching
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supervised by Prof. Dr. Jun Pang. For further information or inquiries, please contact Prof. Dr. Jun Pang directly. Your profile PhD in Computer Science or a related discipline, coupled with outstanding
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The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, or related subject areas Prior experience in large-scale data processing and
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topics: Contribute to the HEXAPIC project Carry out research in the predefined areas Disseminate results in top scientific venues Providing guidance to PhD and MSc students Participating in proposal
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cryptanalysis Side-channel attacks and countermeasures Contributing to the teaching activities of the group (max 90 hours/year) Providing guidance to PhD and MSc students Disseminating results through scientific
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Curriculum vitae Writing sample: either a published journal article or an excerpt from PhD/unpublished draft paper (in which case no longer than 8000 words) Copies of diplomas Names and contact details of two
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contact Julien Schleich, Tel. +352 46 66 44 5337, email: Your profile PhD in Artificial Intelligence, Data Science, Educational Technology, Computer Science, or a related field Solid research background in
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Manage project reporting together with the Reseach support team at the faculty For further information, please contact Julien Schleich, Tel. +352 46 66 44 5337, email: Your profile PhD in Artificial
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for competitive fellowships during their first year with us. The ideal candidate will be recruited by summer 2025. We are particularly seeking postdoc candidates who have recently completed their PhD with a
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-bretagne/ . To be eligible, the applicant must have spent at least 18 months abroad between the 1st of May 2021and the start of the project and have less then 4 years of experience post-PhD. The evaluation