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Causal Inference Machine Learning Postdoctoral Jobs in Highlands Ranch, CO

Seneca Resources Company, LLC

A.I. Engineer

Denver, CO · On-site

$70/hr

AI Engineer (Machine Learning / LLMs / Agentic AI) Location: Merrifield, VA (Hybrid or Remote for ... Optimize models for scalability, inference performance, and production deployment. * Evaluate ...

Judge Group, Inc.

Data Science Engineer

Westminster, CO · On-site

$100K - $140K/yr

... inference latency; identify quantization, pruning, or architectural simplifications that meet deployment constraints. Contribute machine-learning expertise to CONOPS and systems-engineering ...

CACI International, Inc.

AI/ML Engineer

Aurora, CO · On-site

Analyzing large datasets and building models to perform inference * Effective communicator with the ability to write and present technical reports Desired: * MS or PhD in machine learning, computer ...

CACI

AI/ML Engineer with Security Clearance

Aurora, CO · On-site

Analyzing large datasets and building models to perform inference * Effective communicator with the ability to write and present technical reports Desired: * MS or PhD in machine learning, computer ...

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All JobsCausal Inference Machine Learning Postdoctoral JobsCausal Inference Machine Learning Postdoctoral Jobs in Highlands Ranch, CO

Causal Inference Machine Learning Postdoctoral information

See Highlands Ranch, CO salary details

$37.3K

$56.9K

$64K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Aug 12, 2026, the average yearly pay for causal inference machine learning postdoctoral in Highlands Ranch, CO is $56,913.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,200.00 and $59,300.00 per year, depending on experience, location, and employer.

What is a causal inference machine learning postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a causal inference machine learning postdoctoral researcher?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by causal inference machine learning postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What cities near Highlands Ranch, CO are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities near Highlands Ranch, CO with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Highlands Ranch, CO as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $56,913 per year, or $27.4 per hour.

Post-doctoral Researcher - Statistical Learning and Modeling

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

$76K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description

Posting Title
Post-doctoral Researcher - Statistical Learning and Modeling
Location
CO - Golden
Position Type
Postdoc (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The Artificial Intelligence, Learning, and Intelligent Systemsgroup in NLR's Computational Science Center has an immediate opening for a Postdoctoral Researcher to pursue a cross-disciplinary research project in statistical modeling with an emphasis on combining statistics and deep learning.
The candidate will develop statistical and machine learning techniques along with associated software to characterize, model and fuse multiple sources of information. In particular, the candidate will focus on disruptive events and characterize their impacts on infrastructures such as power grids. The successful candidate will be challenged by large datasets, complex interactions of extremes and highly non-linear phenomena.
The candidate will evaluate and communicate results through written research reports and presentations, participate in group meetings and seminars, and assist in engineering and writing statistics and deep learning software, statistical and probabilistic data analysis of results, algorithm design, and publication development.
The candidate will help draft and publish technical reports, conference papers, and journal publications describing the research and is expected to attend and present at technical conferences.
Basic Qualifications
Must be a recent PhD graduate within the last three years.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
Ph.D. in Statistics, Applied Mathematics or Data Science.
  • Demonstrated experience with developing statistical methods, including theoretical foundations, modeling, and computational aspects

  • Demonstrated experience with developing methods for dimension reduction and uncertainty quantification)

  • Demonstrated experience with using deep learning software e.g. pyTorch.

  • Demonstrated experience with handling scientific datasets, eg computer model simulations, observational data

  • Excellent verbal and written scientific comminution skills.

  • Demonstrated experience working with interdisciplinary teams

  • Demonstrated programming experience (python, R) and version control software

Preferred Qualifications
  • Demonstrated experience working on collaborative projects
  • Self-motivated and independent thinker

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $76,600 - $126,400
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; short-term disability insurance*; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verifywww.dhs.gov/E-VerifyFor information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.

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