27 programming-language-"University-of-Oslo" Postdoctoral positions at KINGS COLLEGE LONDON
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Applications are invited for a Research Fellow position on the UKRI-funded Turing AI Fellowship project ‘Event-Centric Framework for Natural Language Understanding’ led by Prof. Yulan He. The 5-year project aims
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associate with expertise in data science to join the King’s BHF Centre of Research Excellence and contribute to a growing cardio-immunology research programme. Inflammation is increasingly recognised as a key
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mechanical design Experience with beam shaping techniques (e.g., spatial light modulators, diffractive optical elements) Proficiency in programming languages like LabVIEW, Python, MATLAB, or C++, and
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housing. Ideally, the candidate will also have language skills and overseas fieldwork experience in a city in one of the project’s focal areas (Greece, Spain, Portugal, Romania, or the USA), experience in
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or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design Previous collaboration with experimental biologists
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United Kingdom Application Deadline 7 Sep 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
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housing. Ideally, the candidate will also have language skills and overseas fieldwork experience in a city in one of the project’s focal areas (Greece, Spain, Portugal, Romania, or the USA), experience in
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imaging data augmentation techniques for robust model design. Strong written and oral communication skills including evidence of publishing peer reviewed research articles. Desirable criteria Experience
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/or interinstitutional research environment. Ability to speak languages relevant to the project, in addition to fluency in English. Website development and administration skills. Experience of research
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of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, general pre-trained transformers, prompt engineering, knowledge graphs, knowledge