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Machine Learning Astronomy Jobs in New York (NOW HIRING)

Socket.dev

Senior Dev Ops Engineer

Manhattan, NY · On-site

$160 - $220/hr

We run Apache Airflow on Astronomer with DAGs that orchestrate high-volume processing across AWS and Kubernetes, including machine learning inference inside pipeline tasks. You will build the ...

Treeswift Inc

Senior Dev Ops Engineer

New York, NY · On-site

$142K - $182K/yr

We run Apache Airflow on Astronomer with DAGs that orchestrate high-volume processing across AWS and Kubernetes, including machine learning inference inside pipeline tasks. You will build the ...

Treeswift Inc

Senior Dev Ops Engineer

Manhattan, NY · On-site

$160 - $220/hr

We run Apache Airflow on Astronomer with DAGs that orchestrate high-volume processing across AWS and Kubernetes, including machine learning inference inside pipeline tasks. You will build the ...

New York University

Software Engineer

New York, NY · On-site

Our group includes researchers from multiple scientific disciplines ranging from machine learning, to astrophysics, biology, neuroscience and quantum computing. The selected candidates will work ...

Polymathic Ai

Research Scientists

Manhattan, NY · On-site

$120 - $250/hr

... astrophysics and biology to solar physics and material sciences. As part of our team, you'll ... Ph.D. in machine learning, computer science, engineering or related technical discipline.

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All JobsMachine Learning Astronomy JobsMachine Learning Astronomy Jobs in New York

Machine Learning Astronomy information

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 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.

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.

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.

How is machine learning used in astronomy?

Machine learning astronomy involves applying algorithms to analyze large datasets from telescopes and space missions, enabling tasks such as identifying celestial objects, classifying galaxies, detecting exoplanets, and predicting cosmic phenomena. Professionals in this field often use tools like Python, TensorFlow, and data analysis techniques to interpret complex astronomical data efficiently.

What are popular job titles related to Machine Learning Astronomy jobs in New York?

For Machine Learning Astronomy jobs in New York, the most frequently searched job titles are:

What job categories do people searching Machine Learning Astronomy jobs in New York look for?

The top searched job categories for Machine Learning Astronomy jobs in New York are:

What cities in New York are hiring for Machine Learning Astronomy jobs?

Cities in New York with the most Machine Learning Astronomy job openings:

Machine Learning Astronomy jobs near you

Joint CUNY - Center for Computational Astrophysics Visiting Scholar

Flatiron Institute

NY • On-site

$70K/yr

Full-time

Re-posted 14 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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