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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
, and biostatisticians. We seek a data scientist to join our team to develop AI/ML-based algorithms to support clinical decision making, hospital performance improvement efforts, and more. This position
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, operating systems, programming languages, formal methods, real-time systems, security and cryptography, and theory of computation and algorithms. In addition, members of the Department collaborate closely
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . To develop novel inertial microfluidics and impedance-based cell sorter. To develop novel label-free CQAs based
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the Unconventional Communications and Computing Laboratory (UC2), led by Dr Michael T. Barros, which develops modelling and algorithmic methods for networked communication and computation under real-world constraints
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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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optical simulation skills (Preferably in Zemax) Strong programming skills (preferably in Python) Experience in deep learning algorithms is a plus Ability to work in a highly international team and
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or other research data. Utilizes and develops algorithms, computational techniques, and statistical methodologies. Helps in the design of new experiments. Implements end-user needs in database searching and
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architecture combining AI accelerators and Genera-Purposes CPUs. Investigate optimization algorithms for customizing the hardware architecture for AI applications Implementation and evaluation as part of a use
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AI algorithms and architectures. Overview The Research Assistant will play a crucial role in facilitating and being responsible for all aspects related to in vivo animal-related work required to
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. The details of the position can be found in the subsequent section. For the Fan lab, please visit https://fanlab.bme.umich.edu/ . Prof. Fan can be reached by his email at xsfan@umich.edu Who We Are At Michigan