Assistant Professor of Computational and Earth System Geosciences

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The Department of Geosciences at Mississippi State University invites applications for a nine-month, tenure-track position at the rank of Assistant Professor. We seek an innovative geoscientist who applies computational, data-driven, and modeling approaches to advance the understanding and prediction of the Earth system.

The position is intentionally broad with respect to disciplinary specialization and is designed to strengthen the department's capabilities in Earth system modeling, prediction, and data-driven geoscience. Areas of interest may include, but are not limited to, atmospheric science and weather prediction, climate science, hydrology, oceanography, coastal processes, environmental variability, and Earth system science. While applicants from all geoscience disciplines are encouraged to apply, candidates whose work contributes to Earth system modeling are particularly encouraged.

We are especially interested in scientists who develop or apply advanced quantitative methods to analyze, model, assimilate, or predict environmental processes across spatial and temporal scales.

Relevant expertise may include computational geoscience, numerical modeling, data assimilation, high-performance computing, geospatial analytics, Earth system modeling, uncertainty quantification, artificial intelligence and machine learning, and data visualization. Candidates are not expected to specialize in all of these areas.

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Research

The successful candidate will establish an externally funded research program within the Department of Geosciences and will have opportunities to participate in ongoing NOAAfunded research conducted through the Northern Gulf Institute (NGI) at Mississippi State University.

The department is particularly interested in candidates whose research advances the observation, modeling, analysis, or prediction of Earth systems, especially with regard to ocean, surface, and atmosphere interactions. Examples include the development or application of Earth-system models; data assimilation methods; geospatial analytics and modeling; artificial intelligence and machine learning techniques; forecasting and prediction systems; or integrated approaches that combine observations, simulations, and data-driven approaches. 

Available research infrastructure includes access to high-performance computing resources and institutional support for computationally intensive and data-rich geoscience research. 

The successful candidate will be expected to develop a research program that complements departmental strengths while fostering collaborations across atmospheric science, geology, hydrology, ocean science, geography, and related disciplines. 
Opportunities also exist for collaboration with NOAA-funded researchers and external partners addressing challenges in environmental monitoring, prediction, and decision support.

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Teaching and Graduate Education

The successful candidate will contribute to undergraduate and graduate education within the Department of Geosciences. Teaching responsibilities will include existing courses aligned with the candidate's expertise as well as the development of new courses that strengthen computational and quantitative training across the geosciences.

Potential instructional areas include Earth system modeling and prediction, data assimilation, geocomputation, high-performance computing, artificial intelligence and machine learning, and geospatial analytics. 

A central goal of this position is to expand opportunities for students across atmospheric science, geography, geology, hydrology, and related disciplines to develop advanced computational and analytical skills that are increasingly essential in the geoscience workforce. 

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Qualifications

Candidates should demonstrate:

• Potential to establish a productive, externally funded research program;
• Expertise in computational, quantitative, or data-driven approaches to geoscience research;
• Experience with or strong interest in Earth system modeling and prediction, data assimilation, scientific computing, artificial intelligence, machine learning, geospatial analytics, or related methodologies;
• Potential to collaborate effectively within interdisciplinary research teams in Geosciences;
• Potential for excellence in undergraduate and graduate teaching and mentoring; and
• Ability to contribute to the Department of Geosciences through research, teaching, graduate education, and service. 

Experience with NOAA-funded research, Earth-system modeling and prediction, high performance computing, or artificial intelligence and machine learning applications is desirable but not required.

MSU is an Equal Opportunity Employer and your advertisement will be compliant with MSU requirements.