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-on experience in autonomous robotics projects; exposure to deep learning or reinforcement learning is a plus. Strong problem-solving ability, collaborative and independent work style, willingness to learn new
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Future. Discover. Together. The Applied Machine Learning (AML) group within the Artificial Intelligence Department is seeking a scientist in the field of Machine Learning to strengthen its research
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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Future. Discover. Together. The Applied Machine Learning (AML) group within the Artificial Intelligence Department is seeking a scientist in the field of Machine Learning to strengthen its research
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for passionate and highly motivated Teaching Faculty. The Undergraduate Division is seeking teaching faculty to teach an undergraduate course, Machines that Create, an introductory yet comprehensive overview
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With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
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Teaching Faculty Position - Machine Learning - Generative AI: Machines that Create Mohamed bin Zayed University of Artificial Intelligence: Academic Appointments: Undergraduate Division Location Abu
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RAP opportunity at National Institute of Standards and Technology NIST Scientific machine learning methods for trustable accelerated materials characterization and design Location Material
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machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant applications, e.g. from neuro- or plant sciences. Advance our understanding
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growing and supportive team with internationally recognized expertise in data management and machine learning. The group has a strong network of national and international collaborators in both academia and