2,428 assistant-professor-computer-science-data-"https:"-"https:"-"https:" Fellowship positions
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papers based on research findings. Developing research proposals related to multi-agent systems and their applications. Job Requirements: PhD degree in Computer Science, Artificial Intelligence, or related
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Posting Information Posting Number FAE1908 Advertised Title Postdoctoral Fellow in Machine Learning and Computational Biology Campus Location Main Campus (Memphis, TN) Position Number 023825
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domain such as computer vision, machine learning, robotics, civil engineering, mechanical engineering, electrical/computer engineering, or a related field. Relevant research experience, including technical
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the instructions for applicants on the ACSPRI Fellowship Program website. About the scholarship PhD candidates at ACSPRI Member Institutions are invited to apply for the 2024-25 ACSPRI Fellowship Program. Valued
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to ensure project deliverables are met. Any ad-hoc duties assigned by Supervisor. Job Requirements Master’s degree in Computer Science, Data Science, Civil/Construction Engineering, Engineering Systems
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delivering the research goals of the group Conduct a research program, defined in agreement with the group Contribute to writing bids for research funding (including facility access) Analyse and interpret data
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WMG, we are undertaking research into how traditional Li-ion battery cell design can be optimised through the application of systems engineering, component modelling and data science. Creating new
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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from the School of Physical and Mathematical Sciences with the School of Chemical and Biomedical Engineering. It is jointly run by the College of Science and the College of Engineering (https
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. Experience with AI/ML algorithms and prediction model development. Familiarity with data structures, algorithms, software engineering best practices, and computational efficiency is highly desirable