Lemont, IL, 60439, USA
56 days ago
Postdoctoral Appointee -Self Driving Laboratories for Earth and Environmental System Science
The Computing, Environment, and Life Sciences directorate (CELS) at Argonne National Laboratory is seeking a postdoctoral scientist to join an exciting project on AI enhances and optimized studies. The appointment will be joint with the Mathematics and Computer Science and Environmental Science divisions. This project will use a variety of steerable, controllable instrumentation (LIDAR, scanning cameras) and rapidly re-deployable in-situ instrumentation to unveil the underlying physics of multi-scale earth system phenomena. We are seeking candidates that have interests in both measurements and modeling. In this role, you can expect to: + Perform leading edge science at the Argonne Testbed for Multiscale Observational Science (ATMOS) + Perform cutting edge research in optimized sensor network design + Instrument integration and programing at the edge + Work onsite 3+ days per week at the Argonne Lemont campus + Along with onsite fieldwork **Position Requirements** **Required knowledge, skills and experience:** + A completed or soon-to-be completed PhD by the beginning of the appointment within the last 0-5 years in Computer Science, Atmospheric or Earth System Science, or related field + Ability to analyze data and model output, strong coding skills preferably in the Python programming language + An understanding of atmospheric modeling + Publication of results in scientific journals and dissemination of findings at meetings + Experience in developing ML/AI models for modeling physical systems, preferably atmospheric and weather phenomena + Exposure to earth system models (eg WRF, land surface modes, hydrological models) to identify sampling strategies for steerable and re-deployable instruments + Ability to distil results into high quality publications + Effective written and verbal communication and teamwork skills + Ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork **Desired knowledge, skills and experience:** + Experience using Pytorch or Tensorflow and similar packages for developing ML/AI models on computer systems across scales + Experience in running WRF + Experience in using high performance computers using tools like Dask + Prior fieldwork experience **Job Family** Postdoctoral Family **Job Profile** Postdoctoral Appointee **Worker Type** Long-Term (Fixed Term) **Time Type** Full time _As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law._ _Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department._ _All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment._
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