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Climate Research Scientist Machine Learning Jobs in Frederick, MD

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Climate Research Scientist Machine Learning information

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$50.2K

$129.4K

$173K

How much do climate research scientist machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for climate research scientist machine learning in Frederick, MD is $129,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,900.00 and $172,000.00 per year, depending on experience, location, and employer.

What does a climate research scientist specializing in machine learning do?

A Climate Research Scientist who specializes in Machine Learning uses advanced algorithms and computational models to analyze climate data and improve predictions about climate change. They work with large datasets from satellites, weather stations, and simulations to identify patterns, make forecasts, and assess environmental impacts. Their work helps inform policy decisions, guide mitigation strategies, and advance our scientific understanding of the Earth's climate system. Collaboration with other scientists, governments, and organizations is often a key part of the role.

What are the key skills and qualifications needed to thrive as a climate research scientist specializing in machine learning?

To thrive as a Climate Research Scientist specializing in Machine Learning, you need a solid background in climate science, statistical analysis, and advanced machine learning techniques, typically supported by a graduate degree in a related field. Experience with programming languages like Python or R, familiarity with climate modeling software, and proficiency in machine learning frameworks such as TensorFlow or PyTorch are highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication skills help you explain complex findings to diverse audiences and collaborate across disciplines. These skills and qualities are crucial for advancing climate research, developing innovative solutions, and informing policy decisions based on robust data analysis.

How do climate research scientists specializing in machine learning typically collaborate with multidisciplinary teams?

Climate Research Scientists with expertise in Machine Learning often work closely with meteorologists, data engineers, environmental scientists, and policy experts. They contribute by developing and refining predictive models using large climate datasets, while also translating complex outputs into actionable insights for decision-makers. Collaboration often involves regular team meetings, joint publications, and integrating domain expertise to ensure that the models are both scientifically robust and practically useful. Strong communication skills are valuable, as these scientists frequently explain technical concepts to colleagues from non-technical backgrounds.

What is the difference between Climate Research Scientist Machine Learning vs Climate Data Analyst?

AspectClimate Research Scientist Machine LearningClimate Data Analyst
Required CredentialsMaster's or PhD in Climate Science, Data Science, or related fields; knowledge of machine learningBachelor's or Master's in Environmental Science, Data Analysis, or related fields; proficiency in data tools
Work EnvironmentResearch labs, universities, environmental agencies, often collaborative and interdisciplinaryGovernment agencies, consulting firms, NGOs; focus on data processing and reporting
Employer & Industry UsageResearch institutions, academia, environmental organizations integrating machine learningPolicy organizations, environmental consultancies analyzing climate data

While both roles involve climate data, Climate Research Scientist Machine Learning focuses on developing predictive models using advanced algorithms, whereas Climate Data Analysts primarily process and interpret climate datasets to inform decisions. The former requires more specialized knowledge in machine learning techniques, while the latter emphasizes data management and reporting skills.

What are popular job titles related to Climate Research Scientist Machine Learning jobs in Frederick, MD?

For Climate Research Scientist Machine Learning jobs in Frederick, MD, the most frequently searched job titles are:

What job categories do people searching Climate Research Scientist Machine Learning jobs in Frederick, MD look for?

The top searched job categories for Climate Research Scientist Machine Learning jobs in Frederick, MD are:

What cities near Frederick, MD are hiring for Climate Research Scientist Machine Learning jobs?

Cities near Frederick, MD with the most Climate Research Scientist Machine Learning job openings:

Climate Research Scientist Machine Learning jobs near you

Assistant Research Scientist (PREP0004898)

Johns Hopkins University

Gaithersburg, MD • On-site

Full-time

Re-posted 4 days ago

Johns Hopkins University rating

8.0

Company rating: 8.0 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

190th of 630 rated colleges and universities

Job description

Description
PREP Research Associate
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). The PREP program provides valuable research and laboratory experience, as well as financial support, to researchers at various stages of their academic and professional careers. Individuals in this position will perform technical work that advances scientific research and measurement science across multiple disciplines.
Research Title: Research Associate - Applied Artificial Intelligence (AI) Scientist for Cybersecurity and Critical Infrastructure
Position Description
The Applied Artificial Intelligence (AI) Scientist for Cybersecurity and Critical Infrastructure will serve as a technical expert in the design, development, evaluation, and deployment of trustworthy AI technologies to enhance the cybersecurity of critical infrastructure systems. The successful candidate will contribute to cutting-edge research initiatives and support the transition of innovative AI-enabled cybersecurity solutions from the laboratory to operational environments.
Key Responsibilities
Responsibilities include, but are not limited to:
Technical Development and Implementation:
• Design, develop, and deploy applied AI solutions focused on strengthening cybersecurity capabilities for critical infrastructure environments.
• Integrate AI technologies into cybersecurity workflows, tools, and operational processes.
Research and Technical Analysis:
• Conduct advanced research and technical analyses to develop and evaluate trustworthy AI approaches for cybersecurity applications.
• Develop methodologies and frameworks that ensure AI systems are robust, secure, explainable, and resilient to adversarial threats.
Technical Collaboration and Coordination:
• Collaborate with researchers and technical experts across NIST and external partner organizations to advance AI-enabled cybersecurity research.
• Evaluate emerging AI technologies and assess their applicability to critical infrastructure cybersecurity challenges.
Technology Transition and Stakeholder Engagement:
• Support the transition of research outcomes into scalable, operational solutions for U.S. industry partners and critical infrastructure stakeholders.
• Contribute to pilot implementations, technology demonstrations, and industry engagement activities that promote adoption of research-based solutions.
Qualifications
• • Experience conducting research and measurement science in artificial intelligence, machine learning, or related fields to address challenges in critical and emerging technology areas, including cybersecurity.
• Experience developing, evaluating, or implementing AI-related guidelines, frameworks, standards, or pilot projects.
• Demonstrated ability to transition research outcomes into practical applications that deliver measurable impact to industry or government stakeholders.
• Knowledge of the NIST AI Risk Management Framework (AI RMF) and related AI guidance documents.
• Strong analytical, technical, and communication skills, with the ability to collaborate effectively in multidisciplinary research environments.
Application Instructions
Please upload the following with your application:
• CV/Resume
*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.
• Self portraits
• Phone number
• Home address/Country
• Citizenship status
• Languages spoken
• Sex/Gender
Privacy Act Statement
Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.

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Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty members, along with their colleagues at the university’s Applied Physics Laboratory, have made us the nation’s leader in federal research and development funding every year since 1979. That’s a fitting distinction for America’s first research university, a place that has revolutionized higher education in the U.S. and continues to bring knowledge and discoveries to the world.

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Headquarters location

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Year founded

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