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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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bioinformatics research coupled with wet-lab investigations, working in the areas of network biology, data-driven hierarchical modeling, and machine learning applied to biomedicine. We also support multiple open
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Doctoral Student - Enhancing Building Efficiency through Edge-based Machine Learning and Control We are looking for a doctoral student to join our international team and contribute to our research efforts
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Post-doctoral Position in Machine Learning
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during the interview process. The Learning Center Computer Attendant provides front-line support for students, faculty, and staff using the library’s computer lab. The attendant ensures a welcoming
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 2 months ago
with a team of engineers, snow scientists, and forest ecologists within the ESRC/EOS at the University of New Hampshire. The appropriate candidate will have cutting edge knowledge of machine learning and
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Applied Mathematics, Computer Science, or Theoretical Physics (at the time of appointment). Background in machine learning theory or in one or more of: high-dimensional probability, random matrix theory
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· Familiarity with applying machine learning techniques and concepts within practical implementations in healthcare domains preferred · Experience with ML frameworks and libraries such as TensorFlow
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Sciences Internal Number: 6463313 AI & Machine Learning Developer University Overview The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education
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such as electrical power. Recent advances in machine learning present new opportunities to enhance the level of fault management and control in NASA's future power system applications. This work aims to