Research Assistant – Gaia Variable Star Machine Learning

UNC-Chapel Hill; North Carolina; On-site; USD 42,000 - 54,000; Full time

Job summary

UNC-Chapel Hill seeks a Research Assistant to support the Gaia Variable Star Machine Learning project. The role focuses on applying machine learning and functional data analysis to map variability in stars using Gaia DR3 multi-epoch photometry and HR diagram data.

You will contribute as the primary day-to-day researcher, coordinating with the PIs and collaborating with the CAS Seed Program team through discovery, characterization, and dissemination phases.

Qualifications

• Research experience with Gaia DR3 multi-epoch photometry or HR diagram/color-magnitude diagram analysis
• Experience with functional data analysis, smoothing splines, or unsupervised clustering methods
• Experience using high-performance computing (e.g., UNC Longleaf) or GPU cloud computing resources
• Familiarity with time-domain survey data (TESS, ZTF, ASAS-SN) or variable star astrophysics
• Experience building interactive web-based data visualization tools

Responsibilities

• Support the CAS Seed Program project: Gaia in Technicolor: mapping variability of stars through ML.
• Serve as primary day-to-day researcher during discovery, characterization, and dissemination phases.
• Work under supervision of project PIs and meet bi-weekly with them.

Skills

Gaia DR3 photometry

HR diagram analysis

Functional data analysis

Smoothing splines

Unsupervised clustering

High-performance computing

GPU cloud computing

Time-domain data

Variable star physics

Interactive visualization

Tools

UNC Longleaf

Job description

Research Assistant – Gaia Variable Star Machine Learning

Position Title Research Assistant – Gaia Variable Star Machine Learning

One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.

University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates for performing arts events.

Primary Purpose of Organizational Unit

Our primary mission is providing instruction of the highest quality in physics and astronomy to undergraduate and graduate students at UNC -CH. Training in physics is fundamental among the natural sciences because it provides understanding of the forces governing the structure of matter, from subatomic particles to the large-scale structure of the universe. Our departmental instructional mission spans all segments of the student community. Over 60% of all college graduates from UNC -CH have taken a course in our department. Among them: undergraduate liberal arts majors who should master the power of quantitative reasoning; undergraduates seeking a degree in another of the natural sciences, who need physics as a foundation for their advanced scientific training; the small number of undergraduates who major in physics, to whom we provide broad and rigorous training. Our graduate education and research advances frontiers of knowledge at the two extremes of space and time, from the very small) the realm of particle physics) to the very large (the realm of astronomy, while expanding the boundaries of knowledge in the many subfields spanning length scales between. Forefront physics and astronomy research requires access to well-equipped laboratories and extensive computing capabilities; it also must be supported by comprehensive and accessible library collections. Again, in research at this advanced level, the bridging aspect of physics provides basic interdisciplinary insight for many other sciences. This instructional mission is supported by a strong managerial, administrative, and technical staff. Duties of these employees range from budget planning and management for the numerous research grants held by faculty in the department to maintaining course and student records. These activities are usually accomplished in a standard 40- hour week schedule.

Position Summary

The Department of Physics and Astronomy seeks a temporary (30 hours/week) Research Assistant to support the CAS Seed Program project ‘Gaia in Technicolor: A Novel Approach for Mapping the Variability of Stars through H-R Diagram Motions’ (PI: Dr. Brad Barlow; Co-I: Dr. Tarek Zikry). The project uses machine learning and functional data analysis to classify millions of variable stars from their motions through the Hertzsprung-Russell diagram in European Space Agency Gaia DR3 multi-epoch photometry. The Research Assistant will serve as the primary day-to-day researcher during the discovery, characterization, and dissemination phases of the project, working under the supervision of Drs. Barlow and Zikry and meeting with them bi-weekly.

Minimum Education and Experience Requirements

Demonstrated possession of the competencies necessary to perform the work.

Management Preferences

• Research experience with Gaia DR3 multi-epoch photometry or H-R diagram/color-magnitude diagram analysis
• Experience with functional data analysis, smoothing splines, or unsupervised clustering methods
• Experience using high-performance computing (e.g., UNC Longleaf) or GPU cloud computing resources
• Familiarity with time-domain survey data ( TESS , ZTF , ASAS -SN) or variable star astrophysics
• Experience building interactive web-based data visualization tools

Optional and Required Documents

Required Documents

• Curriculum Vitae / Resume
• Cover Letter

Optional Documents

Supplemental Questions

Required fields are indicated with an asterisk (*).

Equal Opportunity Employer Statement

The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities.