Basic Purpose/Job Function: 

The NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) is an NSF funded AI Institute that brings together universities, government, and private industry to develop trustworthy AI for environmental science. AI2ES will uniquely benefit humanity by developing novel, physically based AI techniques that are demonstrated to be trustworthy, and will directly improve prediction, understanding, and communication of high-impact environmental hazards.  

We are looking for a Postdoctoral Research Associate with expertise in AI/machine learning, Earth System sciences and ethical and responsible conduct of research.  Ensuring that AI is developed and deployed in an ethical and responsible manner is a key part of creating trustworthy AI. The Postdoctoral Research Associate will extend our work on bias categorizations for Earth Science applications and help to create a bias and risk management framework. 

This Postdoctoral Research Associate position will be located at the University of Oklahoma in Norman, OK (remote work is possible) and will work with Dr. Amy McGovern, the PI and director of the AI2ES institute and Dr Ann Bostrom (co-lead of risk communication for AI2ES, located at the University of Washington).  The Postdoctoral Research Associate will also collaborate with other institute personnel at the University of Oklahoma in the School of Computer Science and the School of Meteorology as well as with personnel across AI2ES. This collaboration will also be in conjunction with NIST and their AI Safety Institute as well as with other agencies including NOAA. 

Position Summary     

The Postdoctoral Research Associate will be a key part of a team that is focused on developing ethical and trustworthy AI for Earth Science applications. The Postdoctoral Research Associate will work with interdisciplinary collaborators across the institute.  At the University of Oklahoma, this will include working with the School of Computer Science and the School of Meteorology as well as colleagues at NOAA and NIST.  This is an exciting position that will allow the Postdoctoral Research Associate to work at the forefront of the development of trustworthy AI and ethical guidelines for the rapidly growing field of AI applied to the Earth Sciences.

Expected job duties

• Research in ethical and responsible trustworthy AI and responsible conduct of research (70% time)

• The postdoc's main duties are to develop and test bias assessment and management strategies and risk management frameworks focused on bias in AI for Earth Science applications.

• Knowledge transfer and institute level integration (15% time)

• The postdoc is expected to integrate with the other postdocs, students, and researchers throughout the institute.  This may involve travel to other institute sites.  It will also involve video meetings with other sites.  Additionally, the postdoc may be involved in working with students.

• Publishing and Sharing results (15% time)

• The postdoc is expected to be actively publishing and presenting results at both AI and atmospheric sciences conferences and journals.  This may involve travel.

Required Job Qualifications   

• Ph.D. in Machine Learning/Artificial Intelligence and experience with atmospheric sciences or a PhD in Atmospheric Science or closely-related field and experience with Machine Learning/Artificial Intelligence.  Note the PhD does not need to be completed to apply for the position but must be completed prior to beginning the postdoc.

• Demonstrated interest and training in ethics and bias assessment/mitigation

• Experience with large spatiotemporal data sets 

• Demonstrated experience of applying at least one machine learning or advanced statistical technique to an atmospheric-science-related problem.

• Demonstrated curiosity, creativity, and enthusiasm to learn new skills.

• Experience pursuing research, both independently and as part of a research team.

• The successful candidate must be legally authorized to work in the United States by the desired start date. AI2ES cannot provide visa sponsorship for this position.

Preferred Job Qualifications  

• Experience with large atmospheric science data sets

• Experience with neural networks/deep learning 

• Prior research studying atmospheric variability, extreme weather, or subseasonal-to-seasonal prediction.

• Prior knowledge of a broad range of ML topics, as demonstrated by classes taken and/or research performed.

• Prior experience collaborating across disciplines.

• Experience with tensorflow (preferred) or pytorch

• Experience with HPC systems

• Experience or interest in working in interdisciplinary teams, including with social scientists

Application Details:

Special Instructions to Applicants -

In your cover letter, please address all of the required and preferred qualifications. A complete application will include a cover letter, resume or CV, and three professional references. References of finalist candidates will be contacted for letters of recommendation; candidates will be notified prior to their references being contacted.

The successful candidate must be legally authorized to work in the United States by the desired start date. AI2ES will not provide visa sponsorship for this position.

If you have a need for hybrid or remote work, please mention that in your cover letter.

This position is for one year, with the option to renew up to 2.5 years total based on performance.

You will submit your application to the link here: http://apply.interfolio.com/151506