23 programming-language-"U" Postdoctoral positions at KINGS COLLEGE LONDON in United Kingdom
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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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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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structured programming language, ideally python, and should have good experience in the analysis of photometric and spectroscopic data of exoplanet atmospheres. The projects will involve the use, modification
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in MATLAB, Python, or other relevant programming languages Motivation to work with animal models Self-motivated, ability to work independently and in a team, willingness to conduct out-of-working hours
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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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in MATLAB, Python, or other relevant programming languages Motivation to work with animal models Self-motivated, ability to work independently and in a team, willingness to conduct out-of-working hours
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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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primary sources and related secondary literature in at least one the target languages is essential, although both languages is preferred. Ability to work with related materials in other languages is an
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scientists, the funders and the public in English Proven ability to keep accurate records and write to a high standard in English * Please note that this is a PhD level role but candidates who have submitted
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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