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Postdoc Research Associate Position in Computati ... (No replies)
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Postdoc Research Associate Position in Computational Materials with AI and Machine learning at the University of South Carolina (USC), USA
Postdoctoral Research Associate opening is available at Machine Learning and Evolution group at the Department of Computer Science and Engineering, the University of South Carolina (USC). This position will be focused on collaborating with computer science teams to develop machine learning, deep learning and AI based computational approaches for discovery of battery materials and metal organic framework (MOF). The postdoc will be jointly supervised by Professor Jianjun Hu (https://scholar.google.com/citations?hl=en&user=_iD3nyMAAAAJ&view_op=list_works&sortby=pubdate) of Computer Science with focus on AI algorithm design and by Professor Ming Hu (https://scholar.google.com/citations?hl=en&user=8Wt2yS0AAAAJ) who specializes in first-principle calculation (DFT and MD).
Our group develops and employs machine learning and AI algorithms together with DFT/MD based computational modeling and simulation techniques for inverse design and discovery of materials (battery and MOF). Our group collaborates closely with computational and experimental materials research groups at USC (especially the Solid Oxide Fuel Cell center), leading to many opportunities for data and AI driven materials discovery. More information about our group can be found at http://mleg.cse.sc.edu.
Qualifications of the candidate:
A wide range of machine learning techniques and deep learning models will be developed in our group via close collaboration between the machine learning team and the computational materials team. We encourage applicants with strong interests in AI+ computational materials to apply. We particularly look for candidates who are good at identifying key challenges in current materials discovery and inverse materials design to be addressed by the latest deep learning and machine learning techniques. We like candidates with strong innovation and passion to bridge fundamental scientific inquiry and high-impact applications by working with our strong AI and deep learning team.
A cover letter, curriculum vitae, representative publications, and a list of references should be sent to Prof. Hu at [email protected]. A starting date of early 2020 is preferred.
University of South Carolina, is located in Columbia, the capital of South Carolina. Our team and our collaborators have been supported with multiple grants from Federal funding agencies including the Department of Energy (DOE), the National Science Foundation (NSF), the National Aeronautics and Space Administration (NASA), the National Institutes of Health (NIH).