Assistant or Associate Professor in Understanding Land-Water-Energy Systems using Machine Learning and Data Analytics

Organization

Pennsylvania State University

Location

University Park, PA

Description

Assistant or Associate Professor in Understanding Land-Water-Energy Systems using Machine Learning and Data Analytics

The College of Earth and Mineral Sciences through the Earth and Environmental Systems Institute (EESI) at The Pennsylvania State University, University Park, PA, seeks to hire tenure-line faculty at the Assistant or Associate rank who study Earth and environmental sciences using new data-driven tools and methods. Candidates for the rank of Associate Professor typically will have several years of research experience and already hold tenure at another institution and/or qualify for immediate tenure at Penn State. Successful candidates will have expertise in at least one of the following areas: data mining, machine learning, artificial intelligence, or deep learning. We seek dynamic scientists who want to teach and lead in the emerging field of data analytics on integrated topics of Earth and environmental science as they relate to land-water and energy systems. Relevant research expertise could include but is not limited to earth imaging (subsurface and surface), water-resource management (physical, chemical, surface and groundwater), decision and policy analysis under uncertainty, natural hazard risk management, energy economics, management and analysis of coupled energy and water systems, and others. We expect the successful candidate to use methods such as machine learning, artificial intelligence, large-data processing, numerical modeling, or remote sensing in order to conduct their work. The position will involve a joint appointment between EESI and either the Department of Energy and Mineral Engineering or Geosciences. The tenure home will be determined based on the research skills and interests of the candidate, after the on-site interviews have been conducted. The selected applicants will be responsible for research and teaching in their respective Departments, along with service for the Department and for EESI. We envision that the new faculty member will offer new courses in data analytics/machine learning/artificial intelligence, aimed especially for graduate and undergraduate students in earth sciences, environmental studies, and science and policy across the College of Earth and Mineral Sciences and the University. Candidates should have earned a Ph.D. in either Earth Science, Geosciences, Geography, Energy Science, Meteorology, Computer Science, Engineering or a related field in the engineering, natural, or social sciences. Candidates must demonstrate expertise and research productivity in data-driven science and show a strong interest in interdisciplinary research and teaching. Excellence in teaching, research, and service is expected of professors employed by Penn State, as is the development of an externally funded research program. Applicants are expected to have completed all requirements of a Ph.D. degree before date of hire. The Pennsylvania State University is committed to and accountable for advancing diversity, equity, and inclusion in all of its forms. We foster a culture of inclusion that supports numerous diversity initiatives and leverages the educational and institutional benefits of diversity. We value inclusion as a core strength and an essential element of our public service mission. To apply, please upload: cover letter; curriculum vitae, including publications list; a description of future research plans; teaching interests; and a statement of commitment towards diversity and inclusion. The review of applications will begin March 1, 2020 and continue until all positions are filled. Inquiries can be sent to Professor Sridhar Anandakrishnan mailto:(sxa17@psu.edu), Chair of the search committee.

Apply online at https://apptrkr.com/1785436

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Penn State is an equal opportunity, affirmative action employer, and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

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