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Machine Learning Astronomy Jobs in Missouri (NOW HIRING)

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 Missouri?

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

Infographic showing various Machine Learning Astronomy job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Tenure-Eligible ASSISTANT/ASSOCIATE/ full PROFESSOR of ELECTRICAL & COMPUTER ENGINEERING / UMKC Scho

UMKC

Kansas City, MO • On-site

Full-time

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Job description

Hiring Department
SCHOOL OF SCIENCE AND ENGINEERING
UNIVERSITY OF MISSOURI - KANSAS CITY
Division of Energy, Matter and Systems
Energy, Matter, and Systems (EMS) is the largest and most academically diverse division in the School of Science and Engineering (SSE). The Division includes the Faculties of Electrical and Computer Engineering (ECE), Mechanical Engineering (ME), Chemistry (CHEM), and Physics & Astronomy (P&A). EMS fosters cross-disciplinary collaborations in both research and education. It has been instrumental in the establishment and continued success of the Missouri Institute of Defense and Energy (MIDE), which has become one of the most successful platforms within the University of Missouri System for sponsored research and collaboration among academia, industry, and government agencies. EMS faculty led efforts to secure multidisciplinary projects and helped UMKC attain the Carnegie R1 status.
https://www.umkc.edu/research/r1.html
https://sse.umkc.edu/research/
The ECE programs in the EMS division have undergone exciting growth in recent years. In addition to the EAC-accredited BS, MS, and PhD programs, the Faculty of ECE plays a key role in several new interdisciplinary programs in Biomedical Engineering, Cybersecurity, and Sustainable Energy Technologies. The Faculty of ECE is highly active in research and holds the record for the most active research grants per tenure-system faculty on the UMKC Campus. In addition to single PI grants, the faculty of ECE also has collaborative projects with the Schools of Pharmacy, Medicine, and Dentistry, and with other STEM and non-STEM units across the campus and beyond. The existing ECE faculty carry out frontier research in Electromagnetics, Optical and Quantum Physics and Engineering, Semiconductors and Next-Generation Electronics, Internet of Things and Future of Computing, Artificial Intelligence and Machine Learning, Electric Power, Renewable Energy, and Control Systems, Signals, Systems, and Communications, Bioelectronics and Intelligent Health Systems. https://sse.umkc.edu/academics/
The SSE recently added a new $40M, 58,000 sq. ft. state-of-the-art facility to support multidisciplinary education, research, and economic development initiatives. Some of the key components of this new facility are NextGen Data Science and Analytics Innovation Center (dSAIC), Augmented and Virtual Reality Lab, Robotics Lab, Motion Capture Lab, UAV & Drone Lab, Innovation Studio & 3D Printing Lab, High-Performance Computing Lab and an Anechoic Chamber . https://sse.umkc.edu/
Job Description
ASSISTANT/ ASSOCIATE/ or FULL PROFESSOR
of Electrical and Computer Engineering
The Division of Energy, Matter and Systems (EMS) in the School of Science and Engineering (SSE) at the University of Missouri-Kansas City (UMKC) is seeking applications and nominations of candidates in the broad areas of quantum computing, wireless communication, robotics, and very large scale integration ( VLSI) and analog systems for a tenure-track/tenure-eligible faculty position in Electrical and Computer Engineering at the Assistant, Associate, or Full Professor level to start in Fall 2027.
Areas of interest for the TT Position: Candidates with backgrounds and expertise in emerging domains, including quantum computing, wireless communication, robotics, and VLSI and analog systems that have strong prospects for extending our sponsored research programs are encouraged to apply. Research in these areas is expected to provide continuous external funding for novel architectures, algorithms, and hardware solutions that address the growing complexity of modern communication networks, autonomous systems, and integrated circuit technologies. These domains include quantum cryptography, quantum analytics, high-performance wireless communication systems, autonomous and cyber-physical robotic platforms, low-power and high-speed VLSI designs, mixed signal and RF circuits, and specialized hardware for sensing, signal processing, and intelligent systems. Successful applicants will have access to the state-of-the-art lab facilities at the SSE, EMS, and the Missouri Institute of Defense and Energy (MIDE). These facilities include several multidisciplinary labs and centers that have supported $75M in externally awarded grants and contracts from various federal agencies, including NSF, DOE, and DOD.
The successful candidates are expected to:
  1. have a strong commitment to teaching undergraduate and graduate courses in ECE and related areas;
  2. develop and sustain an extramurally funded research program;
  3. mentor undergraduate/graduate students and post-doctoral fellows in research and advanced pedagogy;
  4. engage in discipline, division, school, or university services appropriate to the position including serving on graduate committees; and
  5. advance the goals and strategic plans of SSE and UMKC.

Qualifications
All applicants must hold a Ph.D. in Electrical and Computer Engineering or a closely related discipline as of the start date.
Post-doctoral experience is valued.
Applicants for the Associate or full Professor position should have all qualifications of an Assistant Professor, as well as successful grant applications, multiple peer-reviewed publications, mentorship of graduate students or postdoctoral fellows, and strong student evaluations from didactic teaching at their previous position.
Anticipated Hiring Range
Salary is commensurate with rank, credentials, evidence of (or potential for) externally funded research, and experience.
This is a nine-month, benefit-eligible, full-time (1.0 FTE) ranked, faculty appointment eligible for promotion and tenure.
The University of Missouri provides generous leave, health plans, tuition discounts at all 4 UM System universities for full-time employees and qualifying dependents, and retirement contributions. Our academic workloads and schedules promote a positive work/life balance.
Application Materials
For consideration, you must apply online at Careers - Human Resources | University of Missouri-Kansas City , click on Prospective Employees (Job Opening ID 60145).
Please submit the following:
  • cover letter highlighting qualifications for a tenure-track faculty position,
  • curriculum vitae,
  • research statement including successes in externally funded research and PI experience,
  • statement of teaching interests/philosophy and teaching experience, courses taught,
  • the names and current contact information for three professional references.

Please combine all application materials into one PDF or Microsoft Word document and upload as your resume attachment. Limit document name to 50 characters and do not include any special characters (e.g., /, &, %, etc.).
  • If you are experiencing technical problems during application, please email umpshrsupport@umsystem.edu .
  • Please direct all inquiries about the position please contact umkcfacultysearch@umkc.edu at University of Missouri-Kansas City, including the job identification number 60145 and name of the position.
  • Reasonable accommodations may be requested during the application and recruitment process. If you need an accommodation, please contact the Office of Affirmative Action at (816) 235-1323.

Higher education transcripts will be required for candidates advancing as finalists. Candidates will receive prior notification when references will be contacted . After the committee's initial review, all uploaded materials may be shared with all faculty in the EMS division. A Criminal Background Check is required prior to hire.
Application Deadline
Applications will be accepted until a qualified candidate is hired.
Sponsorship Information
Employment visa sponsorship may be available for this position.
Other Information
UMKC is a public, urban, R1 research university with more than 15,000 undergraduate, graduate, and professional students. It is situated in the heart of Kansas City, a vibrant urban community with a Midwestern appeal and an affordable cost of living. Kansas City is a world-class computing and engineering hub, home to companies such as Cerner, Ericsson, IBM, SS&C, Garmin, and Honeywell (defense contracts) that provide enriching educational partnerships for SSE students and faculty. Our university is committed to being a model urban institution recognized for its partnerships with surrounding urban communities, effectively fostering a healthy, safe, and more economically secure quality of life. We are proud to be Kansas City's University. https://www.umkc.edu/
Community Information
A City on the Rise: Big City Life and Midwest Charm, Kansas City offers the best of both worlds - a vibrant, urban community with midwestern appeal and an affordable cost of living. The university is located in a Kansas City metropolitan area that is among the most entrepreneurial cities in America with a population of more than 2.4 million. Our UMKC campuses are centered in the hubs of business activity, cultural arts, (some great barbeque and ethnic cuisine!) and health science research engagement for both the Volker and Health Sciences campuses. Our community boasts championship professional athletic teams, NASCAR racing, a new international airport and a rich history of music and performing arts. Our beautiful state provides rivers, lakes, biking/hiking trails and mountains for outdoor enthusiasts all within an easy drive.
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Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses. For additional information on University benefits, please visit the Faculty & Staff Benefits website at https://www.umsystem.edu/departments-staff/human-resources/benefits-retirement
Equal Employment Opportunity
The University of Missouri is an Equal Opportunity Employer .
To request ADA accommodations, please call the Office of Equity & Title IX at 816-235-6910.

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