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Causal Inference Machine Learning Postdoctoral Jobs in Virginia

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and ... Perform exploratory data analysis, statistical modeling, causal inference, and other advanced ...

Team Velocity

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Machine Learning: XGBoost, LightGBM, Random Forests, Neural Networks, Deep Learning * Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal inference

Team Velocity

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Machine Learning: XGBoost, LightGBM, Random Forests, Neural Networks, Deep Learning * Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal inference

Berkley

Senior Data Scientist

Glen Allen, VA · On-site

Sitting at the intersection of advanced machine learning, software engineering, and business ... Apply causal inference, Bayesian modeling, survival analysis, and simulation to solve high-stakes ...

Berkley

Senior Data Scientist

Glen Allen, VA · On-site

Sitting at the intersection of advanced machine learning, software engineering, and business ... Apply causal inference, Bayesian modeling, survival analysis, and simulation to solve high-stakes ...

Carnegie Mellon University

Data Scientist

Arlington, VA · On-site

They are seeking a Data Scientist to leverage advanced statistics, data analytics, machine learning ... Causal inference / uplift modeling / synthetic controls, Modern ML frameworks: LightGBM/XGBoost ...

Berkley

Senior Data Scientist

Glen Allen, VA · On-site

Sitting at the intersection of advanced machine learning, software engineering, and business ... Apply causal inference, Bayesian modeling, survival analysis, and simulation to solve high-stakes ...

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Causal Inference Machine Learning Postdoctoral information

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 are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Virginia? For Causal Inference Machine Learning Postdoctoral jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Virginia look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Virginia are:
What cities in Virginia are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities in Virginia 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 Virginia as of June 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Biostatistics Postdoctoral Research Associate, Department of Public Health Sciences

University of Virginia

Charlottesville, VA • On-site

Full-time

Re-posted 12 days ago

University Of Virginia rating

7.9

Company rating: 7.9 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

205th of 614 rated colleges and universities

Job description

The Biostatistics Division in the Department of Public Health Sciences in the School of Medicine at the University of Virginia (UVA) is seeking a highly motivated post-doctoral research associate. The research associate will (i) work with Dr. Hong Zhu and a multidisciplinary research team in development and implementation of novel methods for comparative effectiveness research (CER) using complex observational healthcare data, with application to cancer studies; and (ii) collaborate on and support multiple interdisciplinary research projects funded by a multi-institution, NCI-funded, U54 Specialized Program of Research Excellence (SPORE) grant on childhood acute lymphoblastic leukemia, under the supervision of Dr. Hong Zhu, Co-Director of U54 Biostatistics and Data Management Core.
The work for this position will include (i) For CER project: Model multilevel survival data in the presence of confounding and missing data, machine learning approaches as appropriate; Develop computing programs and software; Apply new methods to real-world healthcare data; and (ii) For U54 projects: Plan and conduct database development and data management; Design and perform reproducible statistical analyses for interim and final reports; Assist with abstract and manuscript preparation; Develop and implement innovative procedures in data collection, data management, presentation of results, and statistical analyses. The selected candidate will be expected to participate in the development of publications for peer-reviewed journals and grant proposals to funding agencies.
Postdoctoral employment is temporary and is normally limited to an individual who has been awarded a Ph.D. or equivalent doctorate within the previous five years and who will be involved in full-time research or scholarship at the University. Employment as a Postdoctoral Research Associate is viewed as training and is preparatory for a full-time academic or research career, is supervised by a senior scholar, and allows the appointee to publish the results of his/her research or scholarship during the training period.
Minimum Qualifications
Qualified candidates must have a PhD in biostatistics, statistics, or a related quantitative field, by the appointment start date.
Preferred Qualifications
Strong background and experience in survival analysis, missing data methods, causal inference, machine learning, and clinical biostatistics are preferred, including proficiency in R, SAS/STATA, Python, and/or Markdown. Excellent written and verbal communication skills are required.
Physical Demands
This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.
Salary will be commensurate with education and experience.
This is an exempt-level, benefited position. Learn more about UVA benefits .
This is a restricted position, which is dependent on funding and is contingent upon funding availability. This is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding.
This position is based in Charlottesville, VA, and must be performed fully on-site.
To learn more about UVA and the Charlottesville area, visit UVA Life and Embark CVA .
Application review will begin after May 2, 2026.
Background checks and pre-employment health screenings will be conducted on all new hires prior to employment.
How to Apply
Please apply online , by searching for requisition number R0082712. Complete an application with the following documents:
  • Resume
  • Cover Letter

Upload all materials into the resume submission field. You can submit multiple documents into this one field or combine them into one PDF. Applications without all required documents will not receive full consideration.
Internal applicants: Search and apply for jobs on the UVA Internal Careers website .
Reference checks will be completed by UVA's third-party partner, SkillSurvey, during the final phase of the interview. Five references will be requested, with at least three responses required.
For additional information about the position, please contact Hong Zhu, Professor , at hzhu2m@virginia.edu .
For questions about the application process, please contact Bill Crane, Senior Recruiter, xer5ff@virginia.edu.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .

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About University of Virginia

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The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819

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