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University of California, Berkeley, Department of Electrical Engineering and Computer Sciences Position ID: University of California, Berkeley -Department of Electrical Engineering and Computer
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-electron Schrödinger equation for fermions and bosons with high accuracy and on the application of these methods to problems in the physics of oxides, semiconductors and their surfaces. Machine learning
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of machine learning and deep neural networks Free Probability aspects of Quantum
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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(e.g., finite element or wave propagation simulations) for defect detection and materials analysis Integrate AI, machine learning, and robotics into NDE and manufacturing processes for automation and
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robotics, and human-machine interfaces. We are looking for an ambitious researcher who is looking to use this opportunity to grow towards the next level of research. The position is renewable each year based
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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modeling with AI/machine learning frameworks is a plus Department Unit/Website: www.ameslab.gov Proposed Start Date: October 1, 2025 Proposed End Date or Length of Term: September 30, 2026 Number of Months
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of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for