Postdoc Position in Satellite Remote Sensing and Deep Learning of Energy and Water Resources
The School of Earth Sciences and the Byrd Polar and Climate Research Center at the Ohio State University are seeking one or more researchers, at the postdoctoral or associate levels, to join an interdisciplinary team working on projects in renewable carbon-free energy and water resources combing remote sensing with advanced deep learning techniques. The objective will be to identify and characterize specific Earth surface features at global scales using massive volumes of multiple air and spaceborne remote sensing datasets and deep learning tools, as well as detect and measure changes through time. Tasks will involve continued development of efficient training dataset construction workflows, utilizing ground truth collected by other members of our team, analyses of surface feature morphology and remotely sensed characteristics and development and applications of deep learning methods.
Qualifications: A PhD in relevant Science and Engineering fields (including but not limited to Earth Sciences, Physics, Astrophysics, Computer Science and Engineering, Geography) with demonstrated prior experience in satellite remote sensing and deep learning. Proficiency in python and pytorch are important to work with, and build on, existing tools. As for any postdoc position, excellent organizational and collaborative skills are required, and strong oral and written communication skills are expected. Applications from historically underrepresented minority candidates are particularly welcome.
Job Responsibility: The postdoc will be expected to conduct independent, high-quality research; publish papers; and present work at national and international conferences.
Start date: Negotiable, but soon as possible. Initial appointments are for 12 months with the possibility of multiple annual extensions based on performance and continued funding.
Salary: $60,000/yr. Ohio State provides a comprehensive benefits package ( https://hr.osu.edu/new-employees/employees/benefits-overview/).
To apply: Interested individuals should send a CV, a one-page statement of research interest, and the names and contact information of at least 3 references to Joachim Moortgat at moortgat.1 *at* osu edu. Review of applications will begin immediately and continue until the position is filled. Online applications will also be accepted at this link: https://osu.wd1.myworkdayjobs.com/OSUCareers/job/Columbus-Campus/Post-Doctoral-Scholar_R69357
For more information: contact one of the two faculty advisors on this project:
* Professor Ian Howat (howat.4 *at* osu edu), Director of the Byrd Polar and Climate Research Center, lead on remote sensing. * Associate Professor Joachim Moortgat (moortgat.1 osu edu), lead on deep learning.
Departments: The School of Earth Sciences: https://earthsciences.osu.edu and the Byrd Polar and Climate Research Center: https://byrd.osu.edu
About OSU & Columbus: OSU is the 3rd largest public university in the country with over 60,000 students, and ample resources and opportunities for collaborations. Its campus is situated within Columbus which is a vibrant and fast-growing city with a population of ~1M, but still affordable and easy to navigate. Many postdocs live within walking/biking distance from campus. Columbus/OSU is increasingly becoming a tech hub, e.g., thanks to Intel's forthcoming 20B$ investment, the largest in recent US history, in a nearby chip manufacturing plant, as well as the Ohio Supercomputer Center and various major Big Data and Machine Learning/AI initiatives on campus.
Ohio State University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, disability, ethnicity, gender identity or expression, genetic information, HIV/AIDS status, military status, national origin, race, religion, sex, gender, sexual orientation, pregnancy, protected veteran status, or any other bases under the law. Applicants are encouraged to complete and submit the Equal Employment Identification form.