Position Function
The Department of Earth and Atmospheric Sciences at Cornell University is seeking a Postdoctoral Associate as part of a unique opportunity to develop cutting-edge machine learning and AI techniques for improving drought prediction, seasonal forecasting, and numerical weather and climate modeling. The position is supported outside of traditional funding mechanisms and thus offers the opportunity to develop a significant part of the overall research agenda. The position is intended to offer mentoring to candidates seeking a career in academia or private industry.
The primary focus of this position is to leverage state-of-the-art machine learning and AI algorithms to extract valuable insights from weather forecasting models and/or high-resolution climate datasets, including dynamical, classical statistical, and machine learning-based downscaling. The overarching goal is to improve the usability of weather forecast and climate information for practitioners by better quantifying and communicating uncertainties in regional and local climate forecasts and projections, with a particular emphasis on extreme events.
An important secondary component of the position is knowledge transfer. This offers the opportunity to engage with other research programs within the Department and college and to work with upper-level undergraduates seeking advanced research experience. This aspect offers the opportunity to supervise undergraduate research projects (many of which lead to peer-reviewed publication), organize and conduct programs to expand the proper use and application of machine learning in research across the department, and provide peer mentorship.
This project offers an exciting opportunity to bridge fundamental and applied climate science, allowing you to develop a diverse skill set desirable in both the private and public sectors. You will have the chance to collaborate with renowned institutions such as the National Center for Atmospheric Research (NCAR) and the National Oceanic and Atmospheric Administration’s Geophysical Fluid Dynamics Laboratory (NOAA GFDL), as well as publish research in top-tier journals.
This is a one-year appointment with possible extension contingent on available work, funding, and performance.
This is a full-time position based at Cornell University in Ithaca, New York.
The position includes support for travel to domestic conferences and travel within the United States to collaborate with project partners.
Anticipated Division of Time
- Develop, design, and apply Machine Learning/AI algorithms and workflows for improving weather, seasonal forecasts, and climate model projections in the Northeast. Applications might include (but are not limited to) novel downscaling methods, ensemble post-processing and bias correction, model parameterization, land-atmosphere coupling analysis, and new experimental approaches for synthesizing observational data with model output (40%).
- Write manuscripts and publish results in high-quality, peer-reviewed journals, and present results at conferences and seminars (25%).
- Mentorship and knowledge sharing: activities could include helping to organize department hackathons, assisting graduate and undergraduate students with research projects, guest lectures, etc. (25%).
- Self-directed research and professional development (10%).
Requirements
Required
- Ph.D. in atmospheric science or related field.
- Proficiency in a suite of machine learn algorithms and techniques
- Experience with climate models, seasonal forecast products (e.g., NMME), numerical weather models, or expertise in other aspects of working with large geospatial datasets.
- Excellent written and oral communication skills.
- Evidence of interest in teaching, mentoring, or outreach.
- Ability and desire to pursue research both independently and as part of a team
- Must be able to meet the travel requirements of the position, and have reliable transportation as well as have and maintain a valid and unrestricted New York State driver’s license and be cleared to drive for university business.
Preferred
- Proficiency in Python (preferred) or other data analysis software.
Supervision Exercised
The successful candidate is expected to work with undergraduate and graduate group members on related or different research and provide mentorship and guidance when collaborating. The candidate will not be expected to formally supervise students.
Qualified candidates should submit a short cover letter, curriculum vitae, contact information for three references, and a statement supporting diverse communities (this can be a stand-alone document (preferred) or the information can be embedded in other parts of the application materials) outlining how, through research, teaching, service, mentoring, extension, and/or outreach, the candidate has and will contribute to support Cornell’s historical mission of “any person … any study,” via the website.
Applications will be reviewed as received, continuing until a suitable applicant is identified.
The compensation is $61,008.
