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Machine Learning Astronomy Jobs in Illinois (NOW HIRING)

Senior BI Engineer (Hybrid)

Chicago, IL · On-site +1

$72K - $105K/yr

Architect and enhance ETL/ELT pipelines using Astronomer Airflow and other modern orchestration ... our AI and machine learning-powered Colossus™platform. We serve non-prime consumers and ...

Machine Learning Astronomy information

What is the difference between Machine Learning Astronomy vs Data Scientist?

AspectMachine Learning AstronomyData Scientist
Required CredentialsDegree in Astronomy, Physics, or related fields; knowledge of machine learningDegree in Computer Science, Statistics, or related fields; strong programming skills
Work EnvironmentResearch institutions, observatories, academiaCorporate, tech companies, consulting firms
Industry UsageAnalyzing astronomical data, developing models for celestial phenomenaBusiness analytics, predictive modeling, data visualization

Machine Learning Astronomy focuses on applying machine learning techniques to astronomical data within research settings, while Data Scientists work across various industries analyzing data to inform business decisions. Both roles require strong analytical skills and programming knowledge but differ in domain focus and work environment.

What are 5 potential jobs for astronomy?

Potential jobs for astronomy graduates include research scientist at observatories or universities, data analyst for space agencies, astrophysics researcher, science communicator or educator, and software developer for astronomical data analysis. These roles often require strong analytical skills, programming knowledge, and familiarity with telescopes or data processing tools.

How much do machine learning engineers make at NASA?

Machine learning engineers at NASA typically earn between $90,000 and $150,000 annually, depending on experience, education, and security clearance levels. Salaries may also vary based on location and specific project responsibilities, with some roles requiring expertise in data analysis, programming, and scientific computing tools.

What is machine learning astronomy?

Machine learning astronomy is the application of machine learning techniques to analyze and interpret astronomical data. This field combines computer science, statistics, and astronomy to automate tasks such as classifying celestial objects, detecting anomalies, and predicting astronomical events. With the increasing volume of data from telescopes and space missions, machine learning helps astronomers process and extract meaningful insights more efficiently. Researchers in this area develop algorithms that can learn patterns from vast datasets, leading to new discoveries and a deeper understanding of the universe.

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

To thrive as a Machine Learning Astronomer, you need a strong background in astrophysics, statistical analysis, and programming (often with a PhD in a related field). Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and astronomical data systems is essential. Critical thinking, problem-solving, and effective collaboration are key soft skills for innovating solutions and working within research teams. These skills enable the effective analysis of large astronomical datasets, driving new discoveries and advancements in the field.

Does NASA have machine learning engineers?

NASA employs machine learning engineers to develop algorithms for data analysis, spacecraft navigation, and scientific research. These roles often require expertise in programming, data science, and tools like Python and TensorFlow, with positions available through federal job portals and NASA's career website.

What are some common challenges faced by professionals working in machine learning astronomy?

Machine learning astronomers often encounter challenges such as handling extremely large and complex datasets, ensuring data quality, and effectively preprocessing astronomical data to reduce noise and artifacts. Additionally, interpreting model results in a scientific context can be demanding, as it requires both technical expertise and domain knowledge. Collaboration with astronomers, data engineers, and software developers is essential to ensure that machine learning models are both accurate and scientifically meaningful.

Can AI replace astronomers?

Machine Learning Astronomers use AI to analyze large datasets, identify patterns, and make predictions about celestial phenomena. While AI can automate data processing and assist in research, it does not replace the need for human expertise in designing experiments, interpreting results, and making scientific judgments. The role of astronomers remains essential for guiding AI applications and advancing understanding of the universe.
What cities in Illinois are hiring for Machine Learning Astronomy jobs? Cities in Illinois with the most Machine Learning Astronomy job openings:
Gravitational-Wave Research Scientist III

Gravitational-Wave Research Scientist III

Jet Propulsion Laboratory

Campus, IL

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 25 days ago


Job description

Job Details

New ideas are all around us, but only a few will change the world. That's our focus at JPL. We ask the biggest questions, then search the universe for answers-literally. We build upon ideas that have guided generations, then share our discoveries to inspire generations to come. Your mission-your opportunity-is to seek out the answers that bring us one step closer. If you're driven to discover, create, and inspire something that lasts a lifetime and beyond, you're ready for JPL.

Located in Pasadena, California, JPL has a campus-like environment situated on 177 acres in the foothills of the San Gabriel Mountains and offers a work environment unlike any other: we inspire passion, foster innovation, build collaboration, and reward excellence.

Overview:

The Jet Propulsion Laboratory (JPL), California Institute of Technology, invites applications for a Staff Scientist position working on Gravitational Wave science. JPL offers a unique research environment that bridges the gap between fundamental science and space-mission implementation. We are committed to fostering an enriching, rewarding research environment with strong support for professional and personal development.

Responsibilities:

We are looking for an innovative Scientist III to play a pivotal role in developing data analysis algorithms for the Laser Interferometer Space Antenna (LISA). As JPL expands its capabilities in low-frequency gravitational-wave astronomy, this role is essential for developing the sophisticated pipelines required to untangle complex, overlapping signals in order to transition noisy data into astrophysical insight.

The successful candidate will make contributions in one or more of the following areas:

  • Develop Core Pipelines: Design, implement, and validate novel data analysis algorithms, noise reduction algorithms, low-latency alert pipelines, and global-fit architectures tailored for low-frequency gravitational-wave data.
  • Bridge Theory and Data Integrate instrumental, environmental, and astrophysical systematics into robust statistical frameworks to isolate faint cosmological and astrophysical signals from instrument noise and background signals.
  • Leverage the Caltech-JPL Ecosystem: Actively collaborate with JPL's Galaxies and/or Cosmology Groups, Caltech's Theoretical Astrophysics Relativity (TAPIR) group, and experts across Caltech's Division of Physics, Mathematics, and Astronomy (PMA).
  • Strengthen US LISA ties: Work collaboratively to strengthen ties across the NASA LISA ecosystem at GSFC, MSFC, and JPL.
  • Astrophysical Modeling:Advance and connect theoretical models to data analysis pipelines through development of individual source waveform models and/or astrophysical populations.
  • Shape Long-Term Capabilities: Help develop future space-based mission concepts, ground-segment architectures, and enabling data technologies for the next generation of space physics.

Qualifications:

  • A Ph.D. in Physics, Astronomy, Astrophysics, or a related discipline with a minimum of 3 years of post-doctoral or relevant research experience.
  • Deep technical foundation in gravitational-wave data analysis methodologies.
  • Proven track record of scientific excellence in gravitational-wave astronomy, evidenced by peer-reviewed publications and presentations at major international conferences.
  • Strong interpersonal skills and a demonstrated ability to thrive within a highly collaborative, multi-institutional team environment.
  • Excellent written and verbal communication skills, along with a proactive commitment to fostering an inclusive, diverse, and dynamic research culture.

Desired Skills:

  • Direct experience developing data analysis algorithms, astrophysical models, or software frameworks for gravitational wave observatories.
  • Proficiency in applying machine learning or advanced data science methodologies to complex, continuous astrophysical datasets.
  • Broader expertise in multi-messenger astrophysics or related fields of cosmology (e.g., ground-based GW networks, pulsar timing arrays, or cosmic microwave background analysis).
  • Demonstrated potential or experience in successfully proposing for research funds as a Principal Investigator or Co-Investigator.

Note:

Complete applications must include:

  • Cover Letter: Describing your vision for your role at JPL as a leader and contributor to the field of space-based gravitational-wave science.
  • Curriculum Vitae: Including a bibliography of peer-reviewed and other publications.
  • Research Statement: Detailing your research experience and future research objectives (no more than 3 pages).
  • References: Contact information for at least three professional reference writers.

Applications received by August 15, 2026 will receive full consideration.

JPL has a catalog of benefits and perks that span from the traditional to the unique. This includes a variety of health, dental, vision, wellbeing, and retirement plans, paid time off, learning, rideshare, childcare, flexible schedule, parental leave and many more. Our focus is on work-life balance, and living healthy, fulfilling lives as we Dare Mighty Things Together. For benefits eligible positions, benefits are effective the first day of the month coincident with or immediately following the employee's start date.

For further benefits information click Benefits and Perks

The hiring range displayed below is specifically for those who will work in or reside in the location listed. In extending an offer, Jet Propulsion Laboratory considers factors including, but not limited to, the candidate's job related skills, experience, knowledge, and relevant education/training.

The typical full time equivalent annual hiring range for this job in Pasadena, California.

$144,664 - $180,752

JPL is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, citizenship, ancestry, age, marital status, physical or mental disability, medical condition, genetic information, pregnancy or perceived pregnancy, gender, gender identity, gender expression, sexual orientation, protected military or veteran status or any other characteristic or condition protected by Federal, state or local law.

In addition, JPL is a VEVRAA Federal Contractor.

EEO is the Law.

EEO is the Law Supplement

Pay Transparency Nondiscrimination Provision

The Jet Propulsion Laboratory is a federal facility. Due to rules imposed by NASA, JPL will not accept applications from citizens of designated countries or those born in a designated country unless they are U.S. Citizens, Legal Permanent Residents of the U.S or have other protected status under 8 U.S.C. 1324b(a)(3). The Designated Countries List is available here.