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the common pool of scarce resources. Interested applicants are expected to lead the experimental efforts, though they are also welcome to get involved with modeling aspects of these projects. Typically
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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Intelligence (CIDSAI) and Computational Approaches to Modeling Language (CAMeL) Lab seek to hire a new research assistant to work in any of the CIDSAI/CAMeL research areas, to be involved in the development
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and metabolic disorders. These approaches entail device design and manufacturing, drug conjugation, neuroscience, and preclinical model experiments. The candidate will work in a dynamic
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the frontiers of developmental biology and disease modeling. The laboratory integrates stem-cell biology, fluorescence imaging, bioinformatics, and advanced nano- and micro-engineering to decode organogenesis and
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misuse, analyzing program performance, measuring energy consumption, detecting security vulnerabilities, supporting library migrations, and leveraging large language models (LLMs) for software engineering
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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems
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, Neuroscience, or a related field. A strong background in functional neuroimaging with experience in decoding and/or encoding models is required. Candidates with experience with recurrent neural networks will be
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blind and low-vision individuals in navigating both outdoor and indoor urban spaces. The project's initial phase will employ machine learning models, computer vision algorithms, and real-time sensory
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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems