439 algorithm-development-"Multiple"-"Prof"-"Prof"-"SUNY"-"Simons-Foundation"-"St" positions
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. The research involves the development of machine learning algorithms and MR pulse sequences for next-generation computational MRI. The research will be conducted at the Electrical and Computer Engineering and
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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for the entire university community, where students and staff members will feel supported both in their professional and personal development, within and beyond their multiple identities. To this end, UCY seeks
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Laboratory (ORNL). Major Duties/Responsibilities: Develop models and software for the design and optimization of sensor networks in complex systems, such as water treatment systems Develop physics-based and
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. We have multiple NIH-funded projects to study the influence of FDA-approved GLP-1R agonists on drug seeking and reinstatement in rodents. A newly funded NIH R01 has the goal to determine who may be
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Activity Lab is hiring a full-time lab manager to launch an NIH-funded research study to develop algorithms that use data from wearable sensors to assess the quality of early mother-infant interactions
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an active interest in contributing to our undergraduate game development program. Finally, we are looking for candidates focused on algorithmic theory with an emphasis on improving and expanding
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of the department are to enhance the experience of Barnard CS majors through activities that develop community, provide academic support, and connect to CS-related opportunities outside the classroom; to serve all
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing
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research initiatives by developing and validating clinical phenotypes (i.e., patient or clinical care attributes derived from multiple EHR data sources using an algorithmic approach with a coding framework