324 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation"-"U.S" positions at Carnegie Mellon University
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University Community. UHS performs over 30,000 patient contact visits annually and is a dynamic and collaborative work environment that respects and supports the professional development of its staff. Core
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neuroscience, physics, or related fields is required. Minimum 1-3 years of experience in Monte Carlo simulations. Strong programming skills in Python. Proficiency with Monte Carlo algorithms, reaction-diffusion
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to support faculty in designing and implementing online/hybrid courses and in developing and incorporating technology enhanced learning (TEL) resources in their course design; (iii) analyzing learner/learning
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to support faculty in designing and implementing online/hybrid courses and in developing and incorporating technology enhanced learning (TEL) resources in their course design; (iii) analyzing learner/learning
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for someone who thrives in an interesting and challenging work environment. Core responsibilities include: Developing mathematical models and optimization algorithms for problems arising in ship and vehicle
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development of new programs and initiatives. Working in concert with the Business Administrator and the Associate Director of Academic Affairs, the Director implements solutions and serves as a key information
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on developing innovative algorithms and models to address complex problems in diverse fields such as robotics, healthcare, and finance. The department offers a range of undergraduate and graduate programs
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development of new programs and initiatives. Working in concert with the Business Administrator and the Associate Director of Academic Affairs, the Director implements solutions and serves as a key information
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challenging work environment. We are seeking creative and energetic Academic Program Manager that will be responsible for comprehensive program management of a graduate and/or undergraduate program or multiple
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Theoretic algorithms of defense, and how those can/should be modified to account for human attacker’s biases. To accomplish this goal, we study attacker’s behavior and create cognitive computational models