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Field
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of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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: ● Applicants must have a PhD in Computer Science or related field, with no more than five years post receipt of the PhD. ● Experience in one or more ML domains, such as deep learning, reinforcement learning
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ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in
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communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
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various concepts in welding and related mechanical engineering processes and cleaning existing datasets. Creating deep learning models. Using deep learning to create a robust model that predicts welding
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 2 months ago
inquisitive nature with a deep knowledge of many components listed in this posting and a strong desire for continual learning and growth professionally. We invite candidates to submit an application if able
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Join TUNED and develop the models that will enable engineers to design tunnels in deep clay formations - an essential step in the Netherlands' journey towards safe, long-term disposal of nuclear
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with a deep sea neutrino telescope in Western Pacific Ocean. There will be many exciting opportunities in our group for impactful research at the frontiers of particle physics and astrophysics
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years prior to the application deadline. Experience with machine learning for scientific applications. Experience with deep learning frameworks such as PyTorch or TensorFlow. Experience with atomistic