美國俄克拉荷馬大學2024年招聘博士后職位（氣象學）

俄克拉荷馬大學創(chuàng)建于1890年，是一所位于美國中南部俄克拉何馬州的公立研究型大學。

俄克拉荷馬大學在2021年度《美國新聞與世界報道》大學排名中位列全美第127名，世界第405位，根據(jù)CWUR世界大學排名2021年OU位列世界392名,卡內(nèi)基高等院校分類標準指定的國家最高等級研究型大學。該校石油工程專業(yè)突出，在全美排第4位，是歷史上第一個設(shè)立石油地質(zhì)專業(yè)的高等院校。擁有全球最大的建于大學內(nèi)的自然歷史博物館，其下屬OUMC為全球頂尖醫(yī)學院之一，在器官移植、神經(jīng)外科學等領(lǐng)域均處于國際領(lǐng)先地位。OU會計學以及金融學研究成果優(yōu)秀，根據(jù)楊百翰大學會計學研究排名（BYU Accounting Ranking），2021年該校累計在世界頂級會計學期刊發(fā)表論文的數(shù)量位列世界50名，學校坐落在俄克拉何馬州的諾曼，距離俄克拉荷馬城大都會區(qū)僅有30分鐘的路程。該校畢業(yè)多名杰出校友，其中包括NBA球星特雷·楊,格里芬，新浪網(wǎng)CEO 曹國偉；澳門特別行政區(qū)原特首崔世安；中國科學院“百人計劃”入選者韋昌富；

Postdoctoral Research Associate of Meteorology- Ethical and Responsible AI for Weather and Climate

University of Oklahoma

Job Description

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

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