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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
Responsibilities may include : (1) development and application of statistical and machine learning ... Eric Tchetgen Tchetgen, with a focus on methodological developments for Causal Inference and ...
Responsibilities may include : (1) development and application of statistical and machine learning ... Eric Tchetgen Tchetgen, with a focus on methodological developments for Causal Inference and ...
Post Doc - Open Rank
Worcester, MA · On-site
$62K - $75K/yr
Additional Information Postdoc in Causal Inference of Complex Gene Networks We invite applications ... techniques from machine learning, causal inference, statistics, and algorithms . No prior ...
Post Doc - Open Rank
Worcester, MA · On-site
$62K - $75K/yr
Additional Information Postdoc in Causal Inference of Complex Gene Networks We invite applications ... techniques from machine learning, causal inference, statistics, and algorithms . No prior ...
Post Doc - Open Rank
Worcester, MA · On-site
$75K/yr
Additional Information Postdoc in Causal Inference of Complex Gene Networks We invite applications ... techniques from machine learning, causal inference, statistics, and algorithms . No prior ...
Post Doc - Open Rank
Worcester, MA · On-site
$75K/yr
Additional Information Postdoc in Causal Inference of Complex Gene Networks We invite applications ... techniques from machine learning, causal inference, statistics, and algorithms . No prior ...
Unity's Vector AI team builds machine learning systems for ad targeting across billions of users ... causal inference, A/B testing, and offline evaluation frameworks to measure and improve model ...
Unity's Vector AI team builds machine learning systems for ad targeting across billions of users ... causal inference, A/B testing, and offline evaluation frameworks to measure and improve model ...
Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML ... inference, experimental and quasi-experimental design and analysis, and methods for handling ...
Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML ... inference, experimental and quasi-experimental design and analysis, and methods for handling ...
Postdoctoral Associate Position, Yale School of Public Health and Department of Biostatistics
New Haven, CT · On-site
$49K - $66K/yr
The postdoctoral associate will work with Dr. Bhramar Mukherjee, PhD, the inaugural Senior ... causal inference, machine learning, and artificial intelligence is desirable • Experience with ...
Postdoctoral Associate Position, Yale School of Public Health and Department of Biostatistics
New Haven, CT · On-site
$49K - $66K/yr
The postdoctoral associate will work with Dr. Bhramar Mukherjee, PhD, the inaugural Senior ... causal inference, machine learning, and artificial intelligence is desirable • Experience with ...
In addition, unsupervised machine learning phenomapping techniques will be used to evaluate ... Experience with the application of causal inference methods is preferred * Excellent communication ...
In addition, unsupervised machine learning phenomapping techniques will be used to evaluate ... Experience with the application of causal inference methods is preferred * Excellent communication ...
Leverage model embeddings in causal inference pipelines for health effects and adaptation policy ... Demonstrated expertise in modern machine learning, including at least one of the following: * Deep ...
Leverage model embeddings in causal inference pipelines for health effects and adaptation policy ... Demonstrated expertise in modern machine learning, including at least one of the following: * Deep ...
Postdoctoral Research Fellow
Cambridge, MA · On-site
$70K - $73K/yr
The postdoctoral research fellow will work on causal inference projects under the supervision of Professor Miguel Hernan. The projects range from the development of causal inference and AI methods to ...
Postdoctoral Research Fellow
Cambridge, MA · On-site
$70K - $73K/yr
The postdoctoral research fellow will work on causal inference projects under the supervision of Professor Miguel Hernan. The projects range from the development of causal inference and AI methods to ...
Member of Research Staff (Machine Learning for Neural Circuit Modeling Postdoc)
San Francisco, CA · On-site
The Member of Research Staff role involves developing machine learning models to decode and model ... and causal inference methods to identify candidate circuit mechanisms • Develop models and ...
Member of Research Staff (Machine Learning for Neural Circuit Modeling Postdoc)
San Francisco, CA · On-site
The Member of Research Staff role involves developing machine learning models to decode and model ... and causal inference methods to identify candidate circuit mechanisms • Develop models and ...
2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - Un
Seattle, WA · On-site
Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference ... within Machine Learning. You will tackle challenging, groundbreaking research problems on ...
2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - Un
Seattle, WA · On-site
Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference ... within Machine Learning. You will tackle challenging, groundbreaking research problems on ...
Postdoctoral Research Fellow - Multiomics and Causal Inference
Ann Arbor, MI · On-site
$47K - $65K/yr
This postdoctoral position offers an exceptional opportunity for a highly motivated researcher to lead the hypothesis-driven discovery work of the program's omics and causal inference work streams ...
Postdoctoral Research Fellow - Multiomics and Causal Inference
Ann Arbor, MI · On-site
$47K - $65K/yr
This postdoctoral position offers an exceptional opportunity for a highly motivated researcher to lead the hypothesis-driven discovery work of the program's omics and causal inference work streams ...
Applying offline policy evaluation, counterfactual evaluation, causal inference, or related ... Experience training, evaluating, tuning, and deploying machine learning models across deep learning ...
Applying offline policy evaluation, counterfactual evaluation, causal inference, or related ... Experience training, evaluating, tuning, and deploying machine learning models across deep learning ...
Postdoctoral Associate Position in Pharmacoepidemiology, Perinatal Epidemiology, and Causal Inferenc
New Haven, CT · On-site
Postdoctoral Associate School: Yale School of Public Health Department: Department of Environmental ... inference, starting on February 15th, 2026, or soon thereafter. The position is a one-year ...
Postdoctoral Associate Position in Pharmacoepidemiology, Perinatal Epidemiology, and Causal Inferenc
New Haven, CT · On-site
Postdoctoral Associate School: Yale School of Public Health Department: Department of Environmental ... inference, starting on February 15th, 2026, or soon thereafter. The position is a one-year ...
Postdoctoral Fellow in Biomedical Informatics (Cai Lab)
Cambridge, MA · On-site
$54K - $73K/yr
We are seeking a highly motivated individual with a strong statistical and machine learning ... research focus: 1) Causal inference, invariant learning and representation learning ...
Postdoctoral Fellow in Biomedical Informatics (Cai Lab)
Cambridge, MA · On-site
$54K - $73K/yr
We are seeking a highly motivated individual with a strong statistical and machine learning ... research focus: 1) Causal inference, invariant learning and representation learning ...
Track applied research in causal ML, double machine learning, and agentic/LLM systems; translate ... Deep expertise in causal inference methods: potential outcomes framework, propensity score methods ...
Track applied research in causal ML, double machine learning, and agentic/LLM systems; translate ... Deep expertise in causal inference methods: potential outcomes framework, propensity score methods ...
Post Doc - Open Rank
Worcester, MA · On-site
$48K - $66K/yr
Overview Postdoctoral Position in Population Genetics and Machine Learning of Autoimmunity The ... Developing and applying polygenic risk scores and causal inference models to predict disease onset ...
Post Doc - Open Rank
Worcester, MA · On-site
$48K - $66K/yr
Overview Postdoctoral Position in Population Genetics and Machine Learning of Autoimmunity The ... Developing and applying polygenic risk scores and causal inference models to predict disease onset ...
Causal Inference Machine Learning Postdoctoral information
See salary details
$35.5K - $37.8K
6% of jobs
$37.8K - $40.1K
0% of jobs
$40.1K - $42.5K
0% of jobs
$42.5K - $44.8K
0% of jobs
$44.8K - $47.1K
1% of jobs
$47.1K - $49.4K
4% of jobs
$49.4K - $51.7K
9% of jobs
$52.6K is the 25th percentile. Wages below this are outliers.
$51.7K - $54K
11% of jobs
The median wage is $55K / yr.
$54K - $56.4K
42% of jobs
$56.5K is the 75th percentile. Wages above this are outliers.
$56.4K - $58.7K
21% of jobs
$58.7K - $61K
5% of jobs
$35.5K
$54.2K
$61K
How much do causal inference machine learning postdoctoral jobs pay per year?
As of Aug 5, 2026, the average yearly pay for causal inference machine learning postdoctoral in the United States is $54,223.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,500.00 and $56,500.00 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?
| Aspect | Causal Inference Machine Learning Postdoctoral | Data Scientist |
|---|---|---|
| Required Credentials | PhD in statistics, machine learning, or related field | Bachelor's or Master's in data science, computer science, or related field |
| Work Environment | Academic research, research labs, universities | Corporate, tech companies, startups |
| Industry Usage | Research, academia, specialized industry projects | Business analytics, product development, data-driven decision making |
| Common Search/Comparison | Yes | Yes |
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.
More about Causal Inference Machine Learning Postdoctoral jobs
What cities are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities with the most Causal Inference Machine Learning Postdoctoral job openings:
What states have the most Causal Inference Machine Learning Postdoctoral jobs? States with the most job openings for Causal Inference Machine Learning Postdoctoral jobs include:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs are:
Full-time
Medical, Retirement, PTO
Re-posted 7 days ago
Duke University rating
6.7
Based on 55 frontline employees who took The Breakroom Quiz
483rd of 614 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:
Ideal for candidates who:
analysis
science
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:
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.
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.
Industry
Colleges, universities, and professional schools and hospitals
Company size
10,000+ Employees
Headquarters location
Durham, NC, US