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Alexandria, Virginia. The focus of these positions will be on quantum computing, quantum algorithms, quantum learning, quantum error correction, and quantum fault-tolerance. The successful candidate will join
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developing new algorithmic approaches for TAPS data, interpreting the results in the context of phenotypic observations, and communicating these findings clearly to the broader team. You will prepare the
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, and experience in the algorithms used to analyze these datasets. The appointee will ultimately create an independent research effort with dedicated extramural funding that complements existing strengths
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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support needs of minoritised ethnic people with multiple long-term conditions, and transform how healthcare providers, communities and policymakers construct, respond to, and support them in local and
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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disease into specific subclasses. You will develop AI algorithms to train models that predict if individuals (from which we create circuits) are prone to develop disease and to identify conditions that have
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, applying state-of-the-art sensing technologies and self-developed algorithms. Minimum Qualifications • Ph.D. in Mechanical or Industrial Engineering, and other fields that explore Artificial Intelligence
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and collaborative. The successful applicant will be managing their own academic research and administrative activities. This involves small-scale project management, to co-ordinate multiple aspects