About the Job
The University of Minnesota Twin Cities invites applications for a Postdoctoral Fellow in time-domain and multi-messenger astronomy to work with Prof. Michael Coughlin. The start date is negotiable, with some flexibility. The initial appointment is for one year, with the possibility of annual renewal for up to three years.
Job Duties:
- 50%: Research and development on time-domain and multi-messenger software. Writing, testing, and release of code through the project’s open-source repositories.
- 20%: Supervision of graduate students, technicians, and undergraduates participating in this research.
- 20%: Communicate and coordinate with other personnel involved in the research, including those from non-computing disciplines and with external collaborators.
- 10%: Research in a related discipline of interest to the post-doctoral fellow.
Research Description:
The research will focus on real-time software infrastructure for the Schmidt Observatory System (Argus, DSA, Lazuli, and LFAST) and machine-learning classification of astronomical transients using data from the Zwicky Transient Facility and the Vera C. Rubin Observatory. This includes identifying variable stars and AGN whose variability can mimic transient events. The research will also encompass Bayesian light-curve inference for multi-messenger events, including kilonovae, gamma-ray-burst afterglows, and tidal disruption events. We seek candidates interested in developing machine-learning classifiers, astronomical alert-broker software in Rust, and downstream marshal integrations in Python while contributing to the open-source BOOM and SkyPortal codebases.
Successful participation in these projects will involve collaboration with science teams working in gravitational-wave, optical, and radio time-domain astrophysics, as well as with researchers in computer science and applied machine learning. Postdoctoral Fellows will build strong portfolios demonstrating expertise in real-time AI and large-scale data science for physics and astronomy.
Qualifications
Required Qualifications:
- PhD in Physics, Astronomy, Computer Science, Statistics, Mathematics, or another relevant discipline by the start date of the appointment.
Preferred Qualifications:
- 0-3+ years’ relevant work experience.
- Demonstrated skills (or ability to learn quickly) in any of the following: programming (especially Python and Rust), data science, real-time data pipelines, machine learning and its implementation in data pipelines, and Bayesian inference.
- Prior experience contributing to open-source scientific software.
- Familiarity with alert brokers (BOOM, ANTARES, ALeRCE, Fink, Lasair), target-and-observation managers (SkyPortal, TOM Toolkit, YSE-PZ), or survey pipelines (ZTF, LSST DP0/DP1).
- Familiarity with astronomical time-series analysis, light-curve modeling, or the classification and characterization of variable stars.
- Familiarity with the Open Science Grid or comparable high-throughput compute environments.
- Strong written and verbal communication skills.
- Strong collaboration skills.
- Strong desire to learn new computing platforms.
About the Department
School of Physics and Astronomy: https://cse.umn.edu/physics
Pay and Benefits
Pay Range: $62,232-$70,000 per year; depending on education/qualifications/experience
Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.
- Competitive wages, paid holidays, and generous time off
- Continuous learning opportunities through professional training
- Medical, dental, and pharmacy plans
- Healthcare and dependent care flexible spending accounts
- University HSA contributions
- Disability and life insurance
- Employee wellbeing program
- Financial counseling services
- Employee Assistance Program with eight sessions of counseling at no cost
How To Apply
Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will have the opportunity to complete an online application for the position and attach a cover letter and resume or CV.
This position will remain open until filled.
To request an accommodation during the application process, please e-mail jobcentr@umn.edu.
Diversity
The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.
The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu
Employment Requirements
Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.
About University of Minnesota
The University of Minnesota, Twin Cities (UMTC)
The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023, 2025, 2026), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.
