132 programming-"the"-"DAAD"-"IMPRS-ML"-"PDI-Service"-"U"-"U.S" PhD positions in United States
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programming skills in Python and/or C++ Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments Hands-on experience applying deep learning
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Act of 1990, the University of Tennessee affirmatively states that it does not discriminate on the basis of race, sex, or disability in its education programs and activities, and this policy extends
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should have a Ph.D. in experimental particle physics, excellent data analysis, computing and programming skills and the ability to carry out an independent research program. Prior experience with Machine
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should have a Ph.D. in experimental particle physics, excellent data analysis, computing and programming skills and the ability to carry out an independent research program. Prior experience with CMS will
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the use of leave protected by state or federal law in all programs, activities and employment practices as required by Title IX, other applicable laws, and policies. Retaliation is prohibited by UO policy
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settings, with 5+ years of experience building impactful deep learning systems A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR Strong programming skills in Python and/or C
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The successful applicant will hold a Ph.D. in agricultural economics or related fields. The successful applicant should have experience using statistical programming languages, such as R, Python, SAS, etc
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will also use these results to aid in the testing, evaluation and transition of technologies developed by government-funded research programs. Identify opportunities to apply AI to improve existing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion