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Field
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progress. Ability and willingness to work some flexible hours. Extensive experience in large-scale pre-training of large language model. Experienced in developing machine learning algorithms and large
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Olivier Gossner and funded by an advanced ERC grant. The research themes include information asymmetries and belief hierarchies, encompassing their modeling, applications, and algorithmic aspects. Research
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from chip. Characterise and optimise the algorithm for signal data processing for real-time cell analysis. Develop a user-interface platform for end-user testing of clinical samples. Job Requirements
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quantum spectroscopy, sensing, photonics, semiconductor quantum optics, quantum materials, and quantum algorithms. Postdoctoral Fellows will collaborate with at least one QRI Fellow Mentor. Eligibility
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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manage research datasets, including development of analytic workflows, REDCap data collection tools, algorithm development, and validation of NLP pipelines · lead the development of scholarly outputs
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search strategies and lexicons. Proficiency in fitting and validating statistical models or machine learning algorithms is essential, along with advanced skills in R and/or Python for data processing and
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Responsibilities Participate in the research project to design a microgrid controller for grid interactive building applications. Develop control algorithms for dynamic master selection, coordinating BESS, PV
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particular focus on developing fundamental AI algorithms and methods that can be used in systems for real-time creative and artistic settings. The candidate will be part of a team that creates algorithms
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propulsion, onboard microgrids, EMS algorithms, and real-time validation platforms. Project & Research Responsibilities: Participate in and support the execution of the research project with the Principal