479 algorithm-development-"Multiple"-"Simons-Foundation"-"Embry-Riddle-Aeronautical-University" positions
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(EHR) data built by a multidisciplinary team of software developers, machine learning engineers, clinical researchers and health informaticians. The CogStack team is at the forefront of building
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fundamentally new communications and computing capabilities. Role This post focuses on developing protocols and methodologies aimed at: Efficiently routing entanglement in quantum networks Optimizing quantum
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and Electronics group in the Electrification Section of EEID/ ESTD, at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop and deploy algorithmic tools for monitoring
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University of Massachusetts Medical School | Shrewsbury, Massachusetts | United States | about 3 hours ago
and outliers in claims and develop trends and patterns for potential cases. Develop algorithms, queries, and reports to detect potential FWA activity. Analyze member records and claims data to ensure
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developing machine learning algorithms specifically designed for medical imaging applications. In addition, performs analysis of tissue images of cancer using machine learning methods that have been prototyped
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Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
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aimed at breakthrough innovations in model capabilities, reasoning, safety, and efficiency. Algorithm & Model Development (LLMs & AIGC): Design and develop novel architectures for large-scale language and
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Description The Quantum Information team at UMass Amherst is involved with modeling and optimization of quantum hardware, as well as development of new modeling methods and algorithms, in collaboration with
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that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals. Identify suitable donor options for patients
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy