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. The position is part of COSENSE-2: The Mona Lisa Project, an ambitious program that aims to reinvent therapy selection for metastatic colon cancer using patient-derived mini-tumours (tumouroids), high-content
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Application Deadline 31 Dec 2025 - 00:00 (UTC) Type of Contract Other 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 staff
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Deadline 10 Dec 2025 - 00:00 (UTC) Type of Contract Other 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 staff position
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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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Application Deadline 1 Jan 2026 - 00:00 (UTC) Type of Contract Other 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 staff
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-analytic workflows and historical datasets. Produce high-quality scholarly articles for publication in anthropology, psychology, sociology, and interdisciplinary science journals. Attend lab meetings
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their potential to produce a new generation of ultra-high performance artificial intelligent devices that has ignited researchers’ interest in these remarkable devices. The aim of this position is to
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Country Spain Application Deadline 31 Jan 2026 - 14:00 (Europe/Madrid) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU Research Framework Programme? Not
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subject to performance if the candidate is enrolled in a MSc program – art. 6º, n.4 b) https://diariodarepublica.pt/dr/detalhe/regulamento/950-2019-127238533 https://files.dre.pt/2s/2019/12/241000000
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packages relevant to biostatistics and bioinformatics (e.g. R, Python, Fortran, Matlab, SAS, Stata or equivalent) and experience in the use of high-performance computer resources and parallel computation