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Field
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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exceptional, computationally-minded researchers to help us invent what comes next and, if you are inventive enough, to shape your own direction. If you are a physicist, computer scientist, biologist, engineer
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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, PhDs, and Engineering degrees). These programmes are available through initial training,continuing education, work-study formats, or various accreditation pathways, both on-site and via distancelearning
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material damage assessment 3) Developing AI and machine learning models for robot-assisted laser surgery and validate the model by comparing the results to experimental observations. 4) Support the
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning
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: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders
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. Qualifications Applicants at Postdoctoral Researcher level should hold a PhD in AI enabled learning, educational technology, information systems, computer supported learning, social entrepreneurship, innovation
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, clinical trials, machine learning, optimization, or related methodological areas. Learning and applying deep learning, agentic AI, and other AI methods in assisting research is encouraged. Research
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant