Graduate Funding Information Service

September 21, 2021

Research Assistant: Interdisciplinary, Social, or Behavioral Science for Trustworthy AI in Weather, Climate, and Coastal Oceanography

Application Deadline: September 27, 2021

Interdisciplinary, Social, or Behavioral Science Research Assistant for Trustworthy AI in Weather, Climate, and Coastal Oceanography
  • For a full-time UW graduate student (10+ credit hours per quarter)
  • Compensation includes salary, tuition waiver, and health insurance
  • Requires introductory graduate-level training in statistics, social or behavioral science research methods, and/or machine learning
Department:                                           Evans School of Public Policy & Governance
Date Available:                                     October 1st, 2021
Application Deadline:                        To ensure consideration apply by: September 27th, 2021
General Duties/Description: The Evans School is looking for one graduate research assistant to work with Evans School Professor Ann Bostrom and National Center for Atmospheric Research (NCAR) researchers on risk perception and communication research for the National Science Foundation (NSF) AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). This position is for an average of 20 hours per week, with the possibility of renewal based on performance and funding availability.
·      For full-time UW graduate students
·      Required: A passion for research and introductory graduate-level training in statistics, social or behavioral science research methods, and/or machine learning.
·      Compensation includes salary, tuition waiver, and health insurance
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 the environmental sciences. AI2ES will uniquely benefit humanity by developing novel, physics-based AI techniques that are demonstrated to be trustworthy and will directly improve prediction, understanding, and communication of high-impact environmental hazards.
We are hiring a graduate research assistant (GRA) to assist with research on trust in Artificial Intelligence, especially as applied in weather forecasting and for environmental management. The assistantship is designed to provide an introduction to and training for this type of interdisciplinary research; applicants need not fit all criteria. Applicants with interests and/or experience in risk communication, judgment and decision making, or related social or behavioral sciences will be competitive for the position. Ideally the student will be familiar with machine learning techniques and/or have interests or training in environmental sciences, preferably atmospheric, climate, or ocean sciences. This GRA will be located at the University of Washington in Seattle WA and will work with Dr. Ann Bostrom, a member of the leadership team of AI2ES and PI of the UW subcontract. The GRA will also work closely with other institute personnel at the National Center for Atmospheric Research and across AI2ES.
 
Position Summary
The GRA will be a key part of a team that is developing trustworthy AI for environmental science applications. The GRA will work with this team and its interdisciplinary collaborators across the AI institute, including at NOAA, IBM, and Google. This is an exciting position that will allow the GRA to work at the forefront of the development of trustworthy AI for a variety of environmental science applications to public and private environmental management problems, with a focus on weather and coastal hazards.
The position is part of a large multi-institutional institute that includes graduate students and postdoctoral scholars located throughout the partner institutions. The lead institution is the University of Oklahoma; partners include Colorado State University, the University at Albany, the University of Washington, North Carolina State University, Texas A&M University-Corpus Christi, Del Mar College (Corpus Christi), the National Center for Atmospheric Research, Google, IBM, NVIDIA, Disaster Tech, Vaisala, and the National Oceanic and Atmospheric Administration.
Expected job duties:
·      Research in trustworthy AI for environmental sciences (75% time)
The GRA’s main duties are to work with the team to conduct research and develop methods for assessing and predicting human trust in and use of AI techniques, trustworthy AI, novel explainable AI, and physics-constrained, robust AI methods for environmental sciences. This will involve literature review and synthesis, research design and analysis, and attending a variety of trainings and meetings in order to integrate across diverse disciplinary perspectives. Guidance and training will be provided by the research team leaders and postdoctoral scholars.
·      Knowledge transfer and institute level integration (~10% time)
The GRA is expected to participate in research team meetings and site-wide seminars, and will have the opportunity to integrate with the other postdocs, students, and researchers throughout the AI institute. If possible (post-pandemic), this may involve travel to other institute sites. As part of the AI2ES risk communication research team, the GRA will be involved in working with postdoctoral researchers at the National Center for Atmospheric Research.
·      Publishing and sharing results (~15% time)
The GRA is expected to work with the research team to actively publish and present results at social/behavioral science conferences and journals, and to contribute to interdisciplinary publications and presentations on trustworthy AI in the environmental sciences. This may involve some travel, post-pandemic.
Required Job Qualifications:
·      A passion for research
·      Introductory graduate-level training in statistics, social or behavioral science research methods, and/or machine learning.
·      Demonstrated curiosity, creativity, and enthusiasm to learn new skills.
·      Interest in working on and improving AI for the environmental sciences.
·      Experience pursuing research independently or as part of a research team.
·      The successful candidate must be legally authorized to work in the United States and a student at the University of Washington by the desired start date. AI2ES cannot provide visa sponsorship for this position
Preferred Job Qualifications
·      Experience with research in judgment and decision making and/or science/risk communication.
·      Demonstrated experience of applying at least one qualitative or quantitative research approach to a communications or decision problem.
·      Prior research studying perception or use of models in applied forecasting or management contexts (preferably weather/climate forecasting or environmental management).
·      Prior knowledge of environmental modeling and weather/climate forecasting.
·      Prior knowledge of qualitative and quantitative data analysis approaches.
·      Demonstrated experience applying qualitative analysis techniques or advanced statistical techniques to a communications or decision problem.
·      Prior familiarity with machine learning topics, as demonstrated by classes taken and/or research performed.
·      Prior experience collaborating across disciplines.
 
Diversity Statement:
AI2ES is strongly committed to advancing diversity, equity, and inclusion. Candidates are expected to have the ability to advance the DEI mission and should address this in their statement.
Salary:
Salary and benefits are competitive. Salary is commensurate with academic standing, qualifications, and experience. Appointment includes tuition waiver and medical insurance.
How to Apply:
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 (academic) 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.
Application inquiries may be made by: submitting applications via Handshake or if an Evans Student on EvansJobs and questions about the application system can be directed to evansjob@uw.edu.
Notes: This job classification is governed by a negotiated labor contract and is subject to union shop provisions. For more information about union shop provisions, visit:
Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law.
Per Governor Inslee’s Proclamation 21-14.1, employees of higher education and healthcare institutions must be fully vaccinated against COVID-19 no later than October 18, 2021 unless a medical or religious exemption is approved. Being fully vaccinated means that an individual is at least two weeks past their final dose of an authorized COVID-19 vaccine regimen. As a condition of employment, newly hired employees will be required to provide proof of their COVID-19 vaccination. Updated information about how to provide proof of vaccination or request a medical or religious accommodation will be posted as soon as it is known.