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learning meet in the heart of a global city. We’re the state’s premier public urban research university with more than 100 in-demand, top-ranked bachelor’s, master’s, and doctoral degree programs. We partner
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anticipated that the successful applicant will pursue advanced doctoral training (MD, PhD or MD/PhD) subsequent to this position. Set up, adjust, calibrate, clean, maintain and troubleshoot equipment Clean
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University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. You have a PhD (or are close to completion) in computer science
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in a university or college setting. Working knowledge of the content areas of probability, statistical methods, generalized linear models, statistical computing, and machine learning. Preferred
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on the problem of making distributed machine learning robust to network outages and computational bottlenecks. The work is part of the Norwegian national AI centre SURE-AI, and the PhD student will
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. Experience in artificial intelligence or machine learning approaches applied to materials research will be considered a plus. We regret to inform that only shortlisted candidates will be notified. Hiring
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 1 month ago
skills Specific Requirements The candidate must hold a PhD in machine learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood
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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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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in