Postdoctoral Position in Data Science and Machine Learning: Catalysts Cooperative Institute (NSF HDR)
Catalysts help make chemical reactions go faster and their development impact areas such as energy, the environment, biotechnology, and drug design. However, can catalytic functionality be fully understood without describing the atomic-level structural changes triggered by the molecular interactions of reactants with the catalyst? We investigate this hypothesis by analyzing experimental datasets obtained from both electron microscopy and single-molecule fluorescence resonance energy-transfer spectroscopy, to explore structural dynamics in both nanoparticles and enzymes, by harnessing computational tools from modern statistics and machine learning, and to ultimately perform data-driven discovery of new catalysts.
The Catalysts Cooperative Institute, jointly established by Cornell University and five other institutions as part of the NSF funded Harnessing the Data Revolution (HDR) Big Idea activity, seeks exceptional candidates for a postdoctoral research position in Data Science and Machine Learning at Cornell University. Appointments are renewable up to a total period of two years. The target start date is August 1, 2020, but positions may be filled immediately. Applicants should have completed their PhD by the time of their appointment.
A Cornell appointed postdoc will be mentored by David S. Matteson (email@example.com). Research experience in signal and image processing, dynamical systems, and/or time series analysis is required. All applicants must submit a cover letter, a curriculum vitae including a list of publications, research and teaching statements, and arrange to have two reference letters submitted electronically. Up to two relevant research publications may also be submitted. Application materials must be submitted at: https://academicjobsonline.org/ajo/jobs/15858
Evaluation of applicants will begin February 15, 2020 and continue until the position is filled.
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Internal Number: JOB_POSTING-3-30306
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