Charlottesville, Virginia, United States of America
10 hours ago
Research Associate in Astronomy

The University of Virginia (UVA) invites applications for a Postdoctoral Research Associate position as part of the NSF-Simons AI Institute for Cosmic Origins (CosmicAI) to initiate a comprehensive research program developing training models for explainable AI inference. This research associate would be expected to build, execute and analyze large suites of galaxy formation simulations using varied Dark Matter models. The NSF-Simons AI Institute for Cosmic Origins (CosmicAI) aims to grow transformative AI advances with the overarching goal to increase the accessibility of astronomy data and knowledge for researchers, students, and the public. CosmicAI leverages partnerships between academia (UT Austin, U. of Virginia, U. of Utah, UCLA), national facilities (NSF NRAO and NSF NOIRLab), nonprofits, and industry to develop capabilities that enable astronomical researchers to conceptualize, define, and execute research projects via trustworthy, efficient, robust, and explainable AI methods. By building next-generation AI tools the Institute aims to accelerate discoveries related to the most basic human question: Where do we come from?

CosmicAI Research Associates are expected to participate in departmental activities, mentorship of students, and actively contribute to wider collaboration within the CosmicAI institute. All positions are initially one-year appointments, with renewal for an additional two one-year increments, contingent upon satisfactory performance. A competitive salary and benefits package is offered at UVA. For more information on the benefits available to postdoctoral associates at UVA, visit https://postdoc.virginia.edu and http://hr.virginia.edu/benefits.

QUALIFICATION REQUIREMENTS: Applicants are required to have a Ph.D. in astronomy, physics, or a related field, by the appointment start date.  Candidates with expertise in cosmological simulations with alternative dark matter models are specifically encouraged to apply. Prior experience using machine learning or artificial intelligence is helpful, but not required.

APPLICATION PROCEDURE: Apply online at  https://uva.wd1.myworkdayjobs.com/UVAJobs and attach a single PDF document including a cover letter; curriculum vitae; list of publications; and research statement of no more than three pages (including figures and references) describing the applicant’s past work, synergies with the research focus area described above, as well as potential synergies with the CosmicAI Institute as a whole.

Applicants should also arrange for 3 letters of recommendation to be uploaded directly to https://virginia.app.box.com/f/3dc35a8193864af792fb2d5feb8c38e3 with the file name format

“CandidateLastName_ReferenceLastName.pdf”

APPLICATION DEADLINE: Review of applications will begin on December 15, 2024, but the position will remain open until filled. The University will perform background checks on all new hires prior to employment.

This is a one-year appointment; however, the appointment may be renewed for additional one-year terms, contingent upon available funding and satisfactory performance.

For questions regarding this position, please contact Paul Torrey, Assistant Professor, ygn5rz@virginia.edu .
 

For questions regarding the application process, contact Rich Haverstrom, Academic Recruiter, at rkh6j@virginia.edu.

For more information on the benefits available to postdoctoral associates at UVA, visit postdoc.virginia.edu and hr.virginia.edu/benefits

The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff.  We believe diversity is excellence expressing itself through every person's perspectives and lived experiences.  We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.

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