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enhance machine learning performance; novel chip design strategies prioritizing efficiency and cost; verification of digital designs; advancements in electronic design automation (EDA), especially for AI
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and development of perception stacks for autonomous mobile systems in general in any field Machine learning/deep learning experience applied to perception and any experience with deep Learning
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Graph Machine Learning and Graph Data Management At Section for DATA, Department of Computer Science, Aalborg University, a postdoc position is available. The project is funded by a Novo Nordisk
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approaches. Machine Learning in Geotechnical Engineering: Utilising data-driven approaches to model and predict soil-structure interactions or other complex geotechnical problems. Reliability-Based
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the CliMA team at Caltech for development of a new wildfire module; Generation of reports and scientific publications; Engagement with students and postdocs and provision of technical support within the UNR
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
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for postdocs. UNLV currently employs postdoctoral scholars across a wide range of disciplines. Learn more about UNLV's postdoctoral scholars. MINIMUM QUALIFICATIONS This position requires a PhD in Chemistry
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and machine learning, we collaborate globally to monitor environmental change and support a sustainable future. About the research project The postdoc will work at Chalmers University of Technology in a
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Basque Center for Macromolecular Design and Engineering POLYMAT Fundazioa | Spain | about 1 month ago
the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target