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to Lancaster's high-performance computing facilities. Essential Requirements PhD in Machine Learning, Computer Science, Computational Neuroscience, or related field Demonstrable experience developing deep learning
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collaboration across disciplines, strengthens partnerships with industry and society, and nurtures a thriving global network, who spearheads advancements in AI & Machine Learning, Data Science, Environmental
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Experiential Learning Analyst Apply now Job no: 553801 Work type: Staff Location: Los Angeles Categories: Unit 9 - CSUEU - Technical Support Services, Administrative, Probationary, Full Time Job
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Machine Learning. Situated at the intersection of Computer Science and Mathematics, this role offers a distinct opportunity to drive innovation in one of the most dynamic fields of modern technology. You
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, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project
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PhD studentship in Machine Learning-Based MIMO Radar Sensing for All-Weather Perception in Autonomous Vehicles Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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of education and experience. Job Description: This position is located within the School of Teaching and Learning administrative unit within the College of Education. This position will report to the Office
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
IT EDW Operations Full Time 87012BR Job Summary The Machine Learning and Data engineer role will lead the development, implementation, and maintenance of data pipelines and infrastructure to support
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, and construction of optical systems in the laboratory Documentation and evaluation of experimental and simulation results Development and validation of machine learning algorithms (e.g., CNNs, deep
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate