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Causal Inference Machine Learning Postdoctoral Jobs in Durham, NC

Duke University

Postdoctoral Associate

Durham, NC

The Postdoctoral Associate will train under the primary mentorship of Dr. Tomi Akinyemiju , with ... Familiarity with causal inference methods or machine learning approaches * Demonstrated experience ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

The Postdoctoral Associate will train under the primary mentorship of Dr. Tomi Akinyemiju , with ... Familiarity with causal inference methods or machine learning approaches * Demonstrated experience ...

RTI International

Senior Biostatistician

Raleigh, NC · On-site +1

Demonstrated experience with causal inference methods (e.g., propensity score methods, weighting ... Familiarity with SAS, machine learning, and natural language processing is desirable but not ...

RTI International

Senior Biostatistician

Raleigh, NC · On-site +1

Demonstrated experience with causal inference methods (e.g., propensity score methods, weighting ... Familiarity with SAS, machine learning, and natural language processing is desirable but not ...

Duke University

POSTDOCTORAL ASSOCIATE

Durham, NC

A postdoctoral Research Associate (computational biology and bioinformatics area) position is open ... The ideal candidate will develop novel machine learning and artificial intelligence (ML/AI) methods ...

Duke University

POSTDOCTORAL ASSOCIATE

Durham, NC · On-site

A postdoctoral Research Associate (computational biology and bioinformatics area) position is open ... The ideal candidate will develop novel machine learning and artificial intelligence (ML/AI) methods ...

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Causal Inference Machine Learning Postdoctoral information

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$34.3K

$52.4K

$58.9K

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

As of Jul 28, 2026, the average yearly pay for causal inference machine learning postdoctoral in Durham, NC is $52,396.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,700.00 and $54,600.00 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, and why are they important?

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 are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Durham, NC? For Causal Inference Machine Learning Postdoctoral jobs in Durham, NC, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Durham, NC look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Durham, NC are:
What cities near Durham, NC are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities near Durham, NC 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 Durham, NC as of July 2026, with employment types broken down into 3% Locum Tenens, 81% Full Time, 14% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $52,396 per year, or $25.2 per hour.
Postdoctoral Associate

Postdoctoral Associate

Duke University

Durham, NC

Other

Medical, Retirement, PTO

Posted 29 days ago

Duke University rating

6.7

Company rating: 6.7 out of 10

Based on 55 frontline employees who took The Breakroom Quiz

483rd of 612 rated colleges and universities

Job description

School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,500 faculty physicians and researchers, more than 1,300 students, and more than 6,000 staff, the Duke University School of Medicine along with the Duke University School of Nursing, Duke University Health System and the Private Diagnostic Clinic (PDC) comprise Duke Health. a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.

Be You.

The REGAL (Research to Eliminate GlobAL Cancer Disparities) team at Duke University invites applications for a Postdoctoral Research Associate to join a rigorous, data-intensive research program focused on advancing cancer health equity in the U.S. and globally. This position is designed for scientists with strong computational and quantitative training who are eager to apply advanced epidemiologic and biostatistical methods to complex, multi-level data.

The Postdoctoral Associate will train under the primary mentorship of Dr. Tomi Akinyemiju, with additional support from junior faculty and senior postdoctoral fellows, within a highly collaborative and methodologically driven research environment. The position emphasizes the development and application of advanced analytical approaches to address fundamental questions in cancer disparities, while building a strong foundation for an independent research trajectory.

 

REGAL is a multidisciplinary research program integrating social epidemiology, molecular epidemiology, and global health to investigate the drivers of cancer disparities across the prevention and survivorship continuum. Our work leverages large-scale cohort studies, registry data, and multi-omics platforms to generate actionable, high-impact insights. The team operates at the intersection of epidemiologic theory, quantitative methods, and translational science, with a strong emphasis on rigorous study design, reproducible analytics, and integration of biological and social data.

 

Minimum Requirements:

A PhD degree is required.

Preferred Qualifications:

  • Experience with large-scale or high-dimensional datasets (e.g., cohort, registry, or omics data)
  • Familiarity with causal inference methods or machine learning approaches
  • Demonstrated experience in scientific writing and publication

Ideal for candidates who:

  • Have recently completed (or are near completion of) a doctoral degree in Epidemiology, Biostatistics, or a closely related quantitative field
  • Demonstrate strong computational and statistical training, including experience with complex data

analysis

  • Have proficiency in statistical programming (e.g., R, SAS, STATA, or Python)
  • Have interest or experience in cancer epidemiology, genomics, and/or social determinants of health
  • Exhibit strong critical thinking, attention to detail, and a commitment to rigorous, reproducible

science

  • Are highly motivated, curious, and committed to developing advanced methodological expertise

Be Bold.

Position Description:

Quantitative & Computational Analysis: The Postdoctoral Associate will contribute to the design and execution of analyses addressing cancer disparities using complex, high-dimensional data. This includes implementing advanced statistical and computational methods across diverse data sources such as prospective cohorts, registry datasets, and multi-omics platforms. The role requires strong proficiency in statistical programming, careful attention to analytic assumptions, and the ability to develop reproducible, well-documented workflows.Methodological Development: The Postdoctoral Associate will further develop expertise in advanced epidemiologic and biostatistical methods, including causal inference, survival and longitudinal modeling, and approaches for integrating multi-level and high-dimensional data. There will be opportunities to apply and extend machine learning and data-driven methods, particularly in settings that require combining biological, clinical, and social determinants of health. The position emphasizes strengthening both technical depth and methodological rigor.Research Design & Interpretation: The Postdoctoral Associate will contribute to the development of research questions and analytic strategies that align with the conceptual and methodological goals of the program. This includes critically evaluating study design, identifying potential sources of bias, and ensuring that analytic approaches are appropriate for the research questions. The role requires strong critical thinking and the ability to translate complex analytic results into clear scientific interpretations.Manuscripts & Scientific Communication: The Postdoctoral Associate will lead and contribute to manuscript preparation, including drafting, revising, and submitting scientific papers. The role includes synthesizing complex quantitative findings into clear, rigorous narratives and contributing to abstracts, presentations, and sections of grant applications with mentorship from senior investigators.Collaborative Team Science: The Postdoctoral Associate will work closely with a multidisciplinary team of faculty, analysts, and trainees, contributing to collaborative projects and participating in scientific discussions that strengthen analytic approaches and interpretation. There will also be opportunities to provide guidance to junior trainees and contribute to a supportive and intellectually engaged team environment. Professional Development: The Postdoctoral Associate will engage in structured training and career development activities, including workshops, seminars, and opportunities to develop independent research ideas. The position is designed to support the development of a strong methodological and scientific foundation for future independent funding.

Appointment:

The appointment is for one year and will have the potential to be renewed for another year, based on performance and funding.

Required Application Documents:

  • Current CV
  • Cover letter
  • Statement of research interests
  • Two writing samples (reflecting independent work)
  • Contact Information for three references

 

Choose Duke.

Join our award-winning team as identified by Forbes magazine as America's Best Large Employer 2024 and be part of an inclusive culture that values excellence, innovation, and discovery. As an organization, we have exciting opportunities to be forward-thinking leaders in our field. We want talented individuals to join us, examine our current operations, and create innovative solutions that will revolutionize and enhance the way we approach our work.

Duke University is consistently ranked among the top universities worldwide and is renowned for its cutting-edge research across disciplines.

Beyond the engaging work, you'll also benefit from Duke's competitive benefits package including health insurance plans, generous paid time off, retirement programs with employer contributions, tuition assistance for employees and their children, and more.


Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status.


Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.


Essential Physical Job Functions:

Certain jobs at Duke University and Duke University Health System may include essential job functions that require specific physical and/or mental abilities. Additional information and provision for requests for reasonable accommodation will be provided by each hiring department.


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About Duke University

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Duke is regarded as one of America's leading research universities. Located in Durham, North Carolina, Duke is positioned in the heart of the Research Triangle, which is ranked annually as one of the best places in the country to work and live. Duke has more than 15,000 students who study and conduct research in its 10 undergraduate, graduate, and professional schools. With about 40,000 employees, Duke is the third largest private employer in North Carolina, and it now has international programs in more than 150 countries.

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Colleges, universities, and professional schools and hospitals

Company size

10,000+ Employees

Headquarters location

Durham, NC, US

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