Assistant Professor (Tenure-Track), Artificial Intelligence/Machine Learning/Data Assimilation, Meteorology and Atmospheric Science
The Department of Meteorology and Atmospheric Science in the College of Earth and Mineral Sciences at The Pennsylvania State University, on the University Park campus, invites applications for a tenure-track Assistant Professor in the field of artificial intelligence (AI), machine learning (ML), and/or data assimilation (DA) applications to Meteorology and Atmospheric Science and related fields (MAS). MAS fields include, but are not limited to, traditional meteorology (physical and dynamical, across all scales), atmospheric science, climate science, numerical weather prediction, earth system science (oceans, cryosphere, land surface, carbon cycle), hydrology, atmospheric chemistry, remote sensing, space weather, planetary atmospheres, weather risk and communication, and links to energy and health.
The deluge of large datasets about the Earth and its environment has led to the situation of being data-rich but relatively knowledge poor. Analyzing these large, multi-modal, and heterogenous data requires advanced computational techniques to improve understanding of the governing dynamics and prediction of rare and extreme events. AI/ML/DA methods can be used for more rapid and accurate predictions, pattern recognition, bias correction, model development, model interpretability, data/model fusion, parameter estimation, ensembles, and uncertainty quantification, among other applications.
The candidate can have expertise in any area of MAS but use AI/ML/DA as part of their research, or have AI/ML/DA methods as the focus of their work in MAS. We seek a colleague who will develop a successful, externally funded research program that complements the existing portfolio of the department, teach quality undergraduate and graduate courses, and demonstrate commitment to mentoring, service, and advancing equity and inclusion. A Ph.D. in atmospheric science or a related technical discipline (e.g., meteorology, oceanography, climate science, earth systems science, statistics, computer science, engineering, physics, chemistry, etc.) is required by the time of hire. Demonstrated ability to conduct interdisciplinary research that integrates AI/ML/DA methodologies to application areas is highly desired. This position will support two of Penn State's thematic areas of its strategic plan (https://strategicplan.psu.edu/): ‘Stewarding our Planet's Resources' and ‘Empowering Through Digital Innovation.'
Applications should be submitted online and include (1) a cover letter, (2) statements of research and teaching interests, (3) a curriculum vitae, (4) evidence, either woven through their application materials, or as a separate diversity statement, describing engagement in and plans for fostering a diverse, equitable, and inclusive environment within the department and the professional community, (5) the names and contact information of four references. Applications from candidates that will increase the diversity of the department are strongly encouraged.
Review of applicants will begin on or after December 1st, 2022 and the position will remain open until filled. Further inquiries about the position may be directed to the search committee chair, Associate Professor Steven J. Greybush (sjg213psu.edu).
The College of Earth and Mineral Sciences relies on the expertise, sensitivity and commitment of an inclusive faculty to enhance diversity, seek equity, and create a welcoming environment within our community. We understand that our shared future is guided by basic principles of fairness, mutual respect, and commitment to each other. We are committed to nurturing a learning and working environment that respects differences, including but not limited to, culture, age, gender, race, ethnicity, physical ability, sexual orientation, and religious affiliation. In welcoming every candidate, we strive to meet the needs of professional families by actively assisting with partner-placement needs.
Penn State's Department of Meteorology and Atmospheric Science, part of the College of Earth and Mineral Sciences (EMS), is among the oldest, largest, and most respected meteorology departments in the nation, and is recognized for its exceptional record of leadership in the community and the talented students that it attracts from across the country and around the globe. Penn State also has an Institute for Computational and Data Sciences (ICDS) and a Center for Advanced Data Assimilation and Predictability Techniques (ADAPT) with expertise in AI/ML/DA. The department is located on the University Park campus of Penn State which is in the town of State College, PA. Home to almost 43,000 full-time residents, and commonly called “Happy Valley,” the local area has hundreds of businesses that serve the residents and students alike, including unique shops, restaurants (both local and chain), a variety of supermarkets and big box stores. Additionally, during home football games and the annual Central Pennsylvania Festival of the Arts, State College becomes the third-largest city in Pennsylvania, behind Philadelphia (a 3-hour drive) and Pittsburgh (a 3-hour drive). While surrounded by the forested hills of the Appalachian Mountains, State College is also just a short 3-4 hour drive from New York City, Baltimore, and Washington, DC.
Apply online at https://apptrkr.com/3578317
CAMPUS SECURITY CRIME STATISTICS: For more about safety at Penn State, and to review the Annual Security Report which contains information about crime statistics and other safety and security matters, please go to http://www.police.psu.edu/clery/, which will also provide you with detail on how to request a hard copy of the Annual Security Report.
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.
Copyright ©2022 Jobelephant.com Inc. All rights reserved.