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Machine Learning Astrophysics Jobs (NOW HIRING)

Rockstar Games

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong ... Experience working with pipeline scheduling tools such as Airflow & Astronomer. * Experience ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$105K - $145K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong ... Experience working with pipeline scheduling tools such as Airflow & Astronomer. * Experience ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$124K - $163K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong ... Experience working with pipeline scheduling tools such as Airflow & Astronomer. * Experience ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$105K - $145K/yr

They are seeking a Senior Machine Learning Engineer to join their Analytics team, focusing on ... Astronomer. • Experience working with CI/CD tools such as Terraform and GitHub. • Ability to ...

The Pennsylvania State University

D. in Astronomy, Physics, or a related field is required ... Experience with HPC systems, machine learning, and GRB monitor data analysis would be an advantage.

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How much do machine learning astrophysics jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for machine learning astrophysics in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 per hour, depending on experience, location, and employer.

How do professionals in machine learning astrophysics typically collaborate with domain experts and software engineers on research projects?

In machine learning astrophysics, collaboration is key to successful research outcomes. Professionals in this field often work alongside astrophysicists to ensure that data preprocessing and model outputs align with scientific objectives, while also partnering with software engineers to implement scalable and efficient algorithms. Regular meetings, code reviews, and joint data analysis sessions are common practices, enabling seamless integration of machine learning methods with domain expertise. This multidisciplinary teamwork helps address complex challenges, ensures scientific rigor, and accelerates the development of innovative solutions.

Will AI replace astronomy?

As a Machine Learning Astrophysics professional, AI is a tool that enhances data analysis and discovery in astronomy but is unlikely to fully replace human astronomers. AI automates tasks like data processing and pattern recognition, allowing scientists to focus on interpretation and theory development. Skills in programming, data analysis, and domain knowledge remain essential in this evolving field.

What is the difference between Machine Learning Astrophysics vs Data Scientist in Astrophysics?

AspectMachine Learning AstrophysicsData Scientist in Astrophysics
Required CredentialsPhysics or astrophysics degree, programming skills, machine learning knowledgeStatistics, computer science, or physics degree, programming, data analysis skills
Work EnvironmentResearch institutions, observatories, universitiesResearch projects, data analysis teams in academia or agencies
Industry UsageDeveloping models for astrophysical phenomenaAnalyzing astrophysical data sets for insights

Both roles involve data analysis and programming skills, but Machine Learning Astrophysics focuses on applying machine learning techniques to understand astrophysical phenomena, while Data Scientist in Astrophysics emphasizes broader data analysis and statistical methods within astrophysics research.

How much does NASA pay astrophysicists?

NASA astrophysicists are typically employed as federal government scientists, with salaries based on the General Schedule (GS) pay scale. Entry-level astrophysicists usually earn between GS-11 and GS-12, approximately $55,000 to $90,000 annually, with higher salaries for more experienced roles or those with advanced degrees and specialized skills. Salaries can also include benefits such as health insurance and retirement plans.

What is machine learning astrophysics?

Machine learning astrophysics is an interdisciplinary field that applies machine learning methods to solve complex problems in astrophysics. This involves using algorithms and statistical models to analyze vast amounts of astronomical data, identify patterns, classify celestial objects, and make predictions about cosmic phenomena. Researchers in this area work on projects such as detecting exoplanets, classifying galaxies, or predicting stellar evolution, often leveraging large datasets from telescopes and simulations. The integration of machine learning helps accelerate discoveries by automating data analysis and uncovering insights that would be difficult to find using traditional approaches.

What are the key skills and qualifications needed to thrive as a Machine Learning Astrophysics professional, and why are they important?

To thrive as a Machine Learning Astrophysics professional, you need a strong background in astrophysics, mathematics, and computer science, often supported by a relevant advanced degree such as a PhD. Proficiency with programming languages (like Python), machine learning frameworks (such as TensorFlow or PyTorch), and data analysis tools is essential. Critical thinking, problem-solving, and effective collaboration are vital soft skills for working with interdisciplinary teams and interpreting complex data. These capabilities are crucial for advancing research, uncovering new astrophysical phenomena, and efficiently analyzing large astronomical datasets.

Joint CUNY - Center for Computational Astrophysics Visiting Scholar

Flatiron Institute

NY • On-site

$70K/yr

Full-time

Posted 25 days ago

Job description

Description
The Center for Computational Astrophysics (CCA) is advertising for a Visiting Scholar for a 3-year joint position with the CUNY Graduate Center. The position would require 50% of their time at Flatiron Institute in New York City and 50% their time at the CUNY Graduate Center in New York City. After the 3-year term, the Visiting Scholar would be expected to work full-time as a faculty at the CUNY Graduate Center, as described in a companion advertisement from CUNY. Applications to both positions are required, and it is acceptable to submit identical applications to both. However, applicants are welcome to comment on specific synergies with CCA in their cover letter for the Flatiron application.
The CCA is a dynamic, collaborative, flexible research organization with a mission to advance computational methods, tools, and frameworks that allow scientists to interpret large astronomical datasets and to understand complex, multi-scale physics in astrophysical systems. Current research groups at the CCA include: Astronomical Data, Stars & Plasma Astrophysics, Galaxy Formation, Gravitational Wave Astronomy, Cosmology, Machine Learning & Astrophysics, Exoplanets & Planet Formation, Astronomical Software, and Nearby Universe & Milky Way. There are also multiple cross-group collaborations and projects that cross and/or extend beyond these boundaries. Please see https://www.simonsfoundation.org/flatiron/center-for-computational-astrophysics/ for a full description of research activities at the CCA. CCA scientists are deeply involved in community-building within their research field, the CCA, the Flatiron Institute, and the larger NYC community. Within Flatiron, the CCA benefits from close ties with the Center for Computational Mathematics and superb computational resources and support from the Scientific Computing Core.
As a Visiting Scholar, the successful applicant will be expected to:
  • Lead a vigorous research program;
  • Collaborate with and mentor the CCA's postdoctoral Flatiron Research Fellows and students from the CUNY Masters in Astrophysics;
  • Foster interactions with the broader community (in NYC and beyond) through organizing meetings and workshops;
  • Build intellectual connections across CCA and the Flatiron Institute and beyond;
  • Capitalize on the unique opportunities available at the CCA to further the field of computational astrophysics and/or data analysis, including open source projects and data releases.
  • For reference, the CCA's Mission Statement reads:
  • Solve important, hard problems in computational astrophysics
  • Focus on problems that we at Flatiron are uniquely positioned to solve
  • Invent and propagate better data-analysis practices, analytical methods, and computational methods for the global astrophysics community, with a focus on rigor
  • Develop, maintain, and contribute to open-source software packages, open data, and their communities
  • Create and support a community of astrophysics doers, learners, and mentors in New York City and beyond
  • Train and launch diverse early-career researchers in astrophysics with unique capabilities in computation methods.

ESSENTIAL FUNCTIONS/RESPONSIBILITIES
The successful candidate will be responsible for:
  • Leading a research program with broad and significant impact
  • Mentoring independent postdoctoral fellows and CUNY Masters in Astrophysics candidates
  • Contributing to the scientific strategy, management, and organization of the CCA
  • Fostering scientific communities within CCA, Flatiron, NYC, and beyond.

Qualifications
ducation: Ph.D. degree in a related field
A preferred candidate should have:
  • 1 or more years of postgraduate research experience in astrophysics, with research interests and/or skills that overlap or enhance CCA-relevant interests, broadly defined.
  • Sufficient breadth and flexibility to collaborate broadly within the CCA and especially with its independent postdoctoral fellows.
  • Evidence for scientific impact, assessed in appropriate ways for stage of career and methodology.
  • Demonstrated ability and interest in supervising, mentoring, and collaborating with junior scientists from a variety of backgrounds.
  • Alignment with multiple aspects of the CCA mission statement.

COMPENSATION AND BENEFITS
The annual compensation range for this 0.5 Full time equivalent position is $70,000 in addition to the CUNY Graduate Center faculty salary.
Application Instructions
REQUIRED APPLICATION MATERIALS
  • CV
  • Cover letter
  • Research statement outlining both past research accomplishments and a vision for scientific research
  • Teaching and mentorship philosophy statement for graduate education
  • Contact information for three (3) professional references (name, title, institution, and email address)

Applicants to this position must submit applications both to CUNY and to CCA. The same application can be submitted for the faculty position at the Graduate Center and for the Visiting Scholar position at CCA. However, applicants are welcome to comment on specific synergies with CCA in their cover letter for the Flatiron application.
THE SIMONS FOUNDATION'S DIVERSITY COMMITMENT
Many of the greatest ideas and discoveries come from a diverse mix of minds, backgrounds and experiences, and we are committed to cultivating an inclusive work environment. The Simons Foundation provides equal opportunities to all employees and applicants for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, genetic disposition, neurodiversity, disability, veteran status, or any other protected category under federal, state and local law.

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