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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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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
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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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Cornell University, Electrical and Computer Engineering Position ID: Cornell-ECE-POSTDOC [#31375] Position Title: Position Type: Postdoctoral Position Location: Ithaca, New York 14853
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02215, United States of America [map ] Subject Areas: Computer Science / Artificial Intelligence , Data Science , Machine Learning , Software Engineering Data Science / Artificial Intelligence , Data
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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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the ability to quickly learn new things and work independently, along with previous research experience in at least one of the following areas: 1) statistical genetics/genomics/omics, or 2) deep/machine
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Experience in machine learning Knowledge of SDN and NFV Knowledge of basic TCP/IP protocols What you will do Conduct high-impact research and publish in leading journals and conferences Shape research
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Applications are invited for a position as postdoc in Computational Biology in the laboratory of DNRF Chair and Novo Nordisk Faculty Professor Vijay Tiwari (https://www.tiwarilab.org
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: Machine Learning / Machine Learning Lattice Field Theory lattice gauge theory Nuclear Theory Nuclear astrophysics Appl Deadline: 2026/02/01 11:59PM (posted 2025/11/04) Position Description: Apply