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methods Excellent programming skills and familiarity with modern deep learning frameworks Strong interest in interdisciplinary research, and the ability to engage meaningfully with collaborators from
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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growth methodology based on real-time growth monitoring enabled by advanced in situ characterization tools (RHEED, ellipsometry, curvature measurements, flux monitoring), coupled with machine-learning (ML
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on the interaction between human cognition and language—understood as a cognitive entity, a means of communication, an object of learning and lifelong development, and a sociocultural phenomenon. Mission : Background
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chemistry, bioinformatics, or a related field §you have mastered molecular modeling techniques, machine learning algorithms, and programming languages like Python §you are highly collaborative, with excellent
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innovation player in Luxembourg, dedicated to technological innovation in the fields of environment, information technology, and materials. At the heart of a collaborative ecosystem spanning fundamental
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Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The Machine Learning for Integrative Genomics team (https
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, whilst interacting with a wider, interdisciplinary team within the GEOSIC project. Collaborations within the GEOSIC project are foreseen, with a postdoc in international law who will lead the development
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comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
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cornerstone of the ONCOPLAST project, bridging the complementary expertise of physical-chemists and cell biologists. Within a collaborative and dynamic consortium, the candidate will benefit from active, day-to