Job Description

Application Deadline: This position will be posted until January 25, 2021. Term: This position is a 2-year term position. Relocation: Relocation Assistance is available for this position . Work Authorization: UCAR/NCAR will not sponsor a work visa (e.g., J-1, H1-B, etc.) for this position. U.S. Citizenship, Permanent Residency, or other protected status under 8 U.S.C. 1324b(a)(3) is required for this position. Location: In light of the ongoing coronavirus (COVID-19) pandemic and restricted access to UCAR facilities, UCAR may allow temporary remote work arrangements for newly hired employees. Eventual relocation to UCAR facilities in Boulder, CO is required for this specific position. Full Salary Range: $68,220 Benefits: UCAR affirms its continuing commitment to developing, providing, and administering its employee benefit programs with due consideration for equal employment opportunity and diversity guidelines. UCAR's rich package of employee benefits includes medical, dental, vision, education assistance, retirement, and life insurance. UCAR offers a variety of programs designed to assist with work-life balance including flexible work alternatives, paid time off and 14 weeks of paid parental leave. Where You Will Work: The mission of the Mesoscale and Microscale Meteorology Laboratory is to advance the understanding of the meso- and microscale aspects of weather and climate, and to apply this knowledge to benefit society. What You Will Do: The newly formed NSF Artificial Intelligence (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 hiring two (2) postdoctoral fellows, each for a two-year position, to conduct risk communication, risk perception, and decision-making research with a focus on AI/machine learning for weather, sub-seasonal to seasonal (S2S) climate, and coastal hazards. The postdoctoral fellows will conduct mixed-method, interdisciplinary research to identify and evaluate what trustworthiness means for expert users of AI in their risk management and decision-making contexts, and to iteratively guide and evaluate AI-information development and use. The postdoctoral fellows will be affiliated with UCAR/NCAR and will work with Dr. Julie Demuth, co-lead of the risk communication research for the Institute. The fellows will also work closely with other institute personnel at NCAR and across AI2ES. Responsibilities: Collaborate on developing interview data collection instruments to elicit attitudes, interpretations, and potential uses of AI for different expert groups (weather forecasters, emergency managers, transportation officials, other government users, private industry partners, etc.) across different weather, S2S, and coastal hazards. Collaborate on virtually conducting interviews, analyzing data, and synthesizing findings to guide development of trustworthy AI information. Collaborate on developing a Web-based randomized experimental design to systematically manipulate prototyped AI information and assess effects on experts interpretations, perceptions, and decision-making. Collaborate on virtually conducting experiment, analyzing data, and synthesizing findings to guide development of trustworthy AI information. Collaborate on developing research approach for summative, real-time evaluation of trustworthy AI information by expert groups as part of their real-world decision-making. Curate relevant literature with a focus on trust in risk, decision-making, and AI and other related literature, and ensure continued integration of the literature into the empirical research conducted. Interact with other postdocs, students, and researchers throughout the Institute in order to integrate research perspectives, co-analyze data, and co-develop meaning about implications of results. Prepare results for publication in peer-reviewed journals and for presentation at meetings and conferences. Help prepare and deliver summary reports or project progress reports as needed. What You Need: Education and Years of Experience Ph.D. degree within the last 5 years or expected within the next 6 months in a relevant social science or interdisciplinary field. Desired: Experience working in an academic or professional setting with interdisciplinary teams. General understanding of hazardous weather phenomena. Knowledge, Skills, and Abilities Well-developed knowledge of qualitative and/or quantitative social science research methods, including design, implementation, and analysis of data. Experience conducting qualitative and/or quantitative data collection and analysis in a relevant social science or interdisciplinary field. Demonstrated ability to work independently and as part of an interdisciplinary research team. Skill in developing and implementing project plans to meet goals, objectives, and deadlines for deliverables. Excellent time management and organization skills. Effective written and oral communication skills, both within field of expertise and across disciplinary boundaries. Interest in the interactions between weather/S2S/coastal information and society and/or the interactions between AI/machine learning and society. Desired: Advanced ability in qualitative data analysis and/or statistical analysis. Familiarity with machine learning topics, as demonstrated by classes taken and/or research performed. Applicant Notes: A Cover Letter is required at time of application for this position. An Inclusion Statement will be required for all applicants advancing to an in-person interview. If requested, this statement should address past efforts, as well as future vision and plans to advocate for and advance diversity, equity, and inclusion in the organization and/or field of work. A pre-employment screening is conducted in conjunction with an offer for employment. This screening may involve verifying or reviewing any of the following relevant information: restricted parties screening, employment verification, performance records of internal candidates, education verification, reference checks, verification of professional licenses, certifications, and Motor Vehicle Records. UCAR complies with the Fair Credit Reporting Act (FCRA). Please note that while the position description details both minimum requirements as well as desired skills and experience, we want to remind applicants that you do not need to have all the desired skills and experience to be considered for this role. If you have the passion for the work along with experience in a related field, you are encouraged to apply. We can provide on-the-job training for the rest The University Corporation for Atmospheric Research (UCAR) is an equal opportunity/equal access/affirmative action employer that strives to develop and maintain a diverse workforce. UCAR is committed to providing equal opportunity for all employees and applicants for employment and does not discriminate on the basis of race, age, creed, color, religion, national origin or ancestry, sex, gender, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or pregnancy. Whatever your intersection of identities, you are welcome at the University Corporation for Atmospheric Research (UCAR). We are committed to inclusivity and promoting an equitable environment that values and respects the uniqueness of all members of our organization.,id:36291819},mode:view,requestUri:/en-US/UCAR_Careers/flowController,sessionSecureToken:3hv7b8f5evfchinm1itgibt968,userLanguageCode:en-US,preferredLabelPosition:atopotificationAlertUri:/notifications-alert,pmdFetchTime:0,smdFetchTime:0,structuredDataAttributes:{data:{n title : Postdoc Fellow I - Social or Interdisciplinary Scientist @context : http://schema.org/ @type : JobPosting datePosted : 2021-01-13 description : Application Deadline: This position will be posted until January 25, 2021.

Term: This position is a 2-year term position.

Relocation: Relocation Assistance is available for this position .

Work Authorization: UCAR/NCAR will not sponsor a work visa (e.g., J-1, H1-B, etc.) for this position. U.S. Citizenship, Permanent Residency, or other protected status under 8 U.S.C. 1324b(a)(3) is required for this position.

Location: In light of the ongoing coronavirus (COVID-19) pandemic and restricted access to UCAR facilities, UCAR may allow temporary remote work arrangements for newly hired employees. Eventual relocation to UCAR facilities in Boulder, CO is required for this specific position.

Full Salary Range: $68,220

Benefits: UCAR affirms its continuing commitment to developing, providing, and administering its employee benefit programs with due consideration for equal employment opportunity and diversity guidelines.

UCAR's rich package of employee benefits includes medical, dental, vision, education assistance, retirement, and life insurance. UCAR offers a variety of programs designed to assist with work-life balance including flexible work alternatives, paid time off and 14 weeks of paid parental leave.

Where You Will Work:

The mission of the Mesoscale and Microscale Meteorology Laboratory is to advance the understanding of the meso- and microscale aspects of weather and climate, and to apply this knowledge to benefit society.

What You Will Do:

The newly formed NSF Artificial Intelligence (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 hiring two (2) postdoctoral fellows, each for a two-year position, to conduct risk communication, risk perception, and decision-making research with a focus on AI/machine learning for weather, sub-seasonal to seasonal (S2S) climate, and coastal hazards. The postdoctoral fellows will conduct mixed-method, interdisciplinary research to identify and evaluate what trustworthiness means for expert users of AI in their risk management and decision-making contexts, and to iteratively guide and evaluate AI-information development and use.

The postdoctoral fellows will be affiliated with UCAR/NCAR and will work with Dr. Julie Demuth, co-lead of the risk communication research for the Institute. The fellows will also work closely with other institute personnel at NCAR and across AI2ES.

Responsibilities:

* Collaborate on developing interview data collection instruments to elicit attitudes, interpretations, and potential uses of AI for different expert groups (weather forecasters, emergency managers, transportation officials, other government users, private industry partners, etc.) across different weather, S2S, and coastal hazards. Collaborate on virtually conducting interviews, analyzing data, and synthesizing findings to guide development of trustworthy AI information.
* Collaborate on developing a Web-based randomized experimental design to systematically manipulate prototyped AI information and assess effects on experts interpretations, perceptions, and decision-making. Collaborate on virtually conducting experiment, analyzing data, and synthesizing findings to guide development of trustworthy AI information.
* Collaborate on developing research approach for summative, real-time evaluation of trustworthy AI information by expert groups as part of their real-world decision-making.
* Curate relevant literature with a focus on trust in risk, decision-making, and AI and other related literature, and ensure continued integration of the literature into the empirical research conducted.
* Interact with other postdocs, students, and researchers throughout the Institute in order to integrate research perspectives, co-analyze data, and co-develop meaning about implications of results.
* Prepare results for publication in peer-reviewed journals and for presentation at meetings and conferences. Help prepare and deliver summary reports or project progress reports as needed.

What You Need:

Education and Years of Experience

* Ph.D. degree within the last 5 years or expected within the next 6 months in a relevant social science or interdisciplinary field.

Desired:

* Experience working in an academic or professional setting with interdisciplinary teams.
* General understanding of hazardous weather phenomena.

Knowledge, Skills, and Abilities

* Well-developed knowledge of qualitative and/or quantitative social science research methods, including design, implementation, and analysis of data.
* Experience conducting qualitative and/or quantitative data collection and analysis in a relevant social science or interdisciplinary field.
* Demonstrated ability to work independently and as part of an interdisciplinary research team.
* Skill in developing and implementing project plans to meet goals, objectives, and deadlines for deliverables.
* Excellent time management and organization skills.
* Effective written and oral communication skills, both within field of expertise and across disciplinary boundaries.
* Interest in the interactions between weather/S2S/coastal information and society and/or the interactions between AI/machine learning and society.

Desired:

* Advanced ability in qualitative data analysis and/or statistical analysis.
* Familiarity with machine learning topics, as demonstrated by classes taken and/or research performed.

Applicant Notes:

* A Cover Letter is required at time of application for this position.
* An Inclusion Statement will be required for all applicants advancing to an in-person interview. If requested, this statement should address past efforts, as well as future vision and plans to advocate for and advance diversity, equity, and inclusion in the organization and/or field of work.
* A pre-employment screening is conducted in conjunction with an offer for employment. This screening may involve verifying or reviewing any of the following relevant information: restricted parties screening, employment verification, performance records of internal candidates, education verification, reference checks, verification of professional licenses, certifications, and Motor Vehicle Records. UCAR complies with the Fair Credit Reporting Act (FCRA).
* Please note that while the position description details both minimum requirements as well as desired skills and experience, we want to remind applicants that you do not need to have all the desired skills and experience to be considered for this role. If you have the passion for the work along with experience in a related field, you are encouraged to apply. We can provide on-the-job training for the rest

The University Corporation for Atmospheric Research (UCAR) is an equal opportunity/equal access/affirmative action employer that strives to develop and maintain a diverse workforce. UCAR is committed to providing equal opportunity for all employees and applicants for employment and does not discriminate on the basis of race, age, creed, color, religion, national origin or ancestry, sex, gender, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or pregnancy.

Whatever your intersection of identities, you are welcome at the University Corporation for Atmospheric Research (UCAR). We are committed to inclusivity and promoting an equitable environment that values and respects the uniqueness of all members of our organization.