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Application Deadline 29 Sep 2026 - 02:50 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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peptides Perform and support experimental studies across the METAMIC project, including notably metagenomic sequencing of field study samples (from clinical or environmental use cases) Application
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Application Deadline 24 Sep 2026 - 09:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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infrastructure, and is currently expanding its research activities in exploring several emerging topics of next-generation communications and computing systems. For more details, you may refer to the following
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Application Deadline 30 Oct 2026 - 10:18 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Application Deadline 25 Sep 2026 - 02:50 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Application Deadline 24 Sep 2026 - 10:03 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Application Deadline 29 Sep 2026 - 09:40 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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collaborative opportunities globally, as well as within Luxembourg. The doctoral candidate will perform wet lab experiments as well as computational analysis to uncover biophysical principles that regulate host
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(supervisor) The position holder will be required to perform the following tasks/will do research on the following topics: Software engineering practices for machine learning Tabular machine learning Large