AI for Astrophysics Research Technician

DepartmentPSD Astronomy & Astrophysics: AdministrationAbout the DepartmentThe Department of Astronomy & Astrophysics is focused on teaching, research, and training in the modern field of astrophysics.Job SummaryThis position supports a research project at the intersection of astrophysics, cosmology, and artificial intelligence / machine learning (AI/ML), focused on strong gravitational lensing analysis using simulation-based inference (SBI) with domain adaptation techniques. The work centers on developing robust, transferable inference pipelines that bridge the gap between synthetic simulations and real observational data from large-scale astronomical surveys such as DES and LSST. The research technician will contribute to the design and implementation of deep learning methods aimed at addressing fundamental questions in cosmology, working with large datasets and modern AI/ML inference methods throughout the project.ResponsibilitiesDevelop and benchmark simulation-based inference algorithms (e.g., NPE) for strong gravitational lensing parameter estimation.Implement domain adaptation techniques to improve model robustness and transferability between simulated and real survey data.Generate and curate strong lensing simulations using tools such as lenstronomy or similar ray-tracing frameworks.Train and evaluate deep learning models on simulated datasets and validate performance on realistic or real observational data.Investigate and mitigate systematic biases arising from simulation-to-reality mismatches (sim-to-real gap).Collaborate with team members to integrate inference pipelines into end-to-end analysis workflows.Conduct literature reviews to stay current with advances in SBI, domain adaptation, and strong lensing science.Document code, experiments, and results clearly, maintaining reproducible research practices.Present progress regularly in team meetings and contribute to scientific publications or conference proceedings.Provides technical and administrative support for a research project.Collects and enters data. Assists in analyzing data. Assists with preparation of reports, manuscripts and other documents.Performs other related work as needed.Minimum QualificationsEducation:Minimum requirements include vocational training, apprenticeships or the equivalent experience in related field (not typically required to have a four-year degree).Work Experience:Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.Certifications:-Preferred QualificationsEducation:BSc or MSc degree in astrophysics, physics, computer science or related discipline.Experience:Python programming for scientific applications.Experience with AI/ML algorithms.Technical Knowledge Skills:Computer programming, particularly Python.Preferred CompetenciesExcellent written and oral communication skills.Ability to work in a diverse group that includes students, postdocs, and senior scientists.Ability to juggle multiple tasks.Working ConditionsOffice setting.Application DocumentsResume (required)Cover Letter (required)References (preferred)The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.Job FamilyResearchRole ImpactIndividual ContributorScheduled Weekly Hours37.5Drug Test RequiredNoHealth Screen RequiredNoMotor Vehicle Record Inquiry RequiredNoPay Rate TypeHourlyFLSA StatusNon-ExemptPay Range$27.00 - $30.77The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.Benefits EligibleYesThe University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.Posting StatementThe University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.Job seekers in need of a reasonable accommodation to complete the application process should call View phone number on click.appcast.io or submit a request via Applicant Inquiry Form.All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637. #J-18808-Ljbffr The University Of Chicago