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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize
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the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group
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. The work includes theoretical analysis, algorithm design, and validation on realistic case studies, as well as dissemination of results through publications, open-source code, and collaboration with internal
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will develop algorithms and methods aimed at better detection and mitigation of GNSS interference events from either jamming or spoofing attempts. In addition to research within GNSS integrity
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-film solar cells. LightTrap covers the entire discovery chain, from ab initio calculations and photonic simulations to materials synthesis and nanostructuring, all guided by advanced AI algorithms
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, the candidate will be leading the building of a database to i) guide neuroethological studies (behaviour and physiology) in honeybees at University of Konstanz, and ii) train algorithms aimed at modelling and
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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit, and excellent collaboration skills. You will be responsible for the collection
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algorithms for speech enhancement using state-of-the-art machine learning techniques. You will design and evaluate models that leverage phoneme-level or discrete speech representations and conduct experiments