Post-doctoral researchers are being sought to work alongside SDS Associate Professor David Matteson on three individual data science initiatives. Short project descriptions and links to the individual Academic Jobs postings are listed below. Please see Academic Jobs for the full listing.
Greater Data Science Cooperative Institute
The Greater Data Science Cooperative Institute (GDSC), jointly established by Cornell University (CU) and the University of Rochester (UR) as part of the NSF funded HDR TRIPODS program, seeks exceptional candidates for postdoctoral research positions at Cornell (note: UR has a simultaneous and coordinated, but separate search). Appointments are renewable up to a total period of three years. The target start date is August 1, 2020, but positions may be filled immediately.
GDSC is based on two founding tenets: that enduring advances in data science require combining techniques and viewpoints across electrical engineering, mathematics, statistics, and theoretical computer science; and, that data-science research must be grounded in an application domain. Cross-disciplinary research directions include: (i) Topological Data Analysis; (ii) Data Representation; (iii) Network & Graph Learning; (iv) Decisions, Control & Dynamic Learning; and, (v) Diverse & Complex Modalities. GDSC specifically aims to consider applications in medicine and healthcare, a major strength of CU and UR, and one for which advances in data science can have a direct, positive impact on society. Applicants should have completed their PhD in a discipline listed above (or related) by the time of their appointment. Some background or interest in biomedicine and/or healthcare would be an advantage.
The PRISM Cooperative Institute
The natural-human world is characterized by highly interconnected systems, in which a single discipline is not equipped to identify broader signs of systemic risk and mitigation targets. In particular, what risks in agriculture, ecology, energy, finance and hydrology are heightened by climate variability and change? Recent advances in computing and data science, and the data revolution in each of these domains have now provided a means to address these questions.
The PRISM Cooperative Institute, jointly established by Cornell University and nine other institutions (see: sites.google.com/view/prism-prj ) including Columbia University 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.
Catalysts Cooperative Institute
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.