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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. Record of peer-reviewed publications. Knowledge in one or more of the following areas is
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 1 hour ago
atmospheric science, physics, and computer science. Experience in analyzing satellite data and geospatial data are desired. Skills in AI, machine learning, deep learning, keras, Pytorch are preferred. A proven
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environment to its 37,000 students (FTEs) and 8.700 employees and has an annual revenue of EUR 1.106 billion. Learn more at www.international.au.dk/ Where to apply Website https://AU.emply.net/recruitment
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of Pharmacy, UCC, led by the Professor of Pharmaceutics, Brendan Griffin is aiming to develop Artificial Intelligence (AI) and machine learning tools that can accelerate the creation of medicines for conditions
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: Artificial intelligence applied to seismics, neural networks, machine learning, synthetic data generation, seismic inversion, geological CO2 storage. Abstract: This research project aims to develop a synthetic
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, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any
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and extension center in Twin Falls, plus Extension offices in 42 counties. One of the nation’s land-grant research universities, U of I is a noted national leader in student-centered learning and
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compulsory education for their children. Please contact and confirm your supervisor before applying. Contact information for eligible supervisors can be found at https://math.bnu.edu.cn/jzg/szdw/index.htm
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, dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand principles and mechanisms underlying distributed brain network computations through the dual
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the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins