ZipRecruiter

Log In

1

Causal Inference Machine Learning Postdoctoral Jobs in Indianapolis, IN

Elevance Health

Gen AI Engineer

Indianapolis, IN · Hybrid

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning ... LLM caching strategies for inference optimization; RAG architecture design and implementation.

Elevance Health

Gen AI Engineer

Indianapolis, IN · Hybrid

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning ... LLM caching strategies for inference optimization; RAG architecture design and implementation.

Elanco

Senior Research Scientist

Indianapolis, IN

$94K - $120K/yr

Collaborate with Computational Sciences to develop machine learning models for hit expansion and ... of postdoctoral training. * Experience: Professional experience in industry research and early ...

New

next page

Showing results 1-20

All JobsCausal Inference Machine Learning Postdoctoral JobsCausal Inference Machine Learning Postdoctoral Jobs in Indianapolis, IN

Causal Inference Machine Learning Postdoctoral information

See Indianapolis, IN salary details

$33.9K

$51.8K

$58.3K

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

As of Aug 11, 2026, the average yearly pay for causal inference machine learning postdoctoral in Indianapolis, IN is $51,830.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,100.00 and $54,000.00 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 are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Indianapolis, IN? For Causal Inference Machine Learning Postdoctoral jobs in Indianapolis, IN, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Indianapolis, IN look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Indianapolis, IN are:
What cities near Indianapolis, IN are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities near Indianapolis, IN with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you

Postdoctoral Fellow in Biostatistics and Health Data Science

Indiana University School of Medicine

Indianapolis, IN

$46K - $63K/yr

Full-time

Re-posted 14 days ago

Job description

Postdoctoral Fellow in Biostatistics and Health Data Science

Indiana University is an equal opportunity employer and provider of ADA services and prohibits discrimination in hiring. See Indiana University's Notice of Non-Discrimination here which includes contact information.

The Annual Security and Fire Safety Report, containing policy statements, crime and fire statistics for all Indiana University campuses, is available online. You may also request a physical copy by emailing IU Public Safety at iups@iu.edu.

Posting Details

Title - Postdoctoral Fellow in Biostatistics and Health Data Science

Appointment Type - Postdoctoral Fellow

Department - IUSM - Biostatistics

Campus - IU School of Medicine Indianapolis

Position Summary - Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare, multimodal data analysis (EHRs, medical imaging, omics, physiological signals, clinical notes), and causal AI (causal inference, discovery, counterfactual reasoning). The successful candidate will collaborate with an interdisciplinary team of computer scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations.

Key responsibilities include:

  • Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines.
  • Build reproducible research pipelines and maintain reliable experiment codebases (prefer Python).
  • Apply causal inference and discovery frameworks to clinical questions.
  • Translate proposed methods and frameworks into real-world clinical workflows.
  • Contribute to grant proposals and research reports.

This is an exciting opportunity to join a fast growing BHDS Department with 36 faculty members and more than 50 professional staff. We are dedicated to excellence in biostatistical, health data science, and informatics research and education. We have an extensive portfolio of research programs in related areas. Our NIH funding as principal investigators and co-investigators has been ranked among the top in the nation. The Department currently has an ongoing PhD program in Biostatistics, MS program in Biostatistics, and BS program in Health Data Science. We have established strong collaborations with both clinical and basic science research departments and divisions and health systems including IU Health and Eskenazi Hospitals as well as strong partnerships with major research institutes and centers including Regenstrief Institute, Center for Computational Biology and Bioinformatics, Indiana Clinical and Translational Science Institute (CTSI), Indiana University Simon Comprehensive Cancer Center, Indiana Institute of Biomedical Research, and Indiana Alzheimer's Disease Research Center. Additional details about the Department and the PhD program are available on our web page: https://medicine.iu.edu/biostatistics.

The Indianapolis Campus is the focal point of health professions education at Indiana University, and the School of Medicine is the country's second largest allopathic medical school. Indianapolis consistently ranks high nationally on many of the "best places to live" lists and has an economy that is growing in the life sciences arena. In addition, it has always been one of the cities with the lowest cost of living. Carmel, Indy's northern neighbor, was recently named as the best mid-sized city in the country.

IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.

Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the largest concentrations of health sciences companies in the nation. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life – the city possesses a variety of professional sports, arts venues and outdoor recreation areas. Residents of this dynamic city, and surrounding suburbs, enjoy leading educational systems and top-ranked universities, paired with a diverse population. Indianapolis International Airport is a top-ranked international airport, being named "Best Airport in North America" by Airports Council International for many years. For additional information on life in Indy: https://faculty.medicine.iu.edu/relocation.

The search will continue until the positions are filled.

Basic Qualifications - Required Qualifications:

  • Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
  • Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
  • Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
  • Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
  • Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.

Preferred Qualifications:

  • Experience with LLMs/foundation models (e.g., clinical NLP, retrieval-augmented generation, instruction tuning) and multimodal transformers.
  • Solid understanding of causal methods (e.g., propensity scores, IPW, matching) and/or causal discovery.
  • Familiarity with data engineering and MLOps (e.g., SQL, Spark, Airflow, Docker, Kubernetes).
  • Knowledge of responsible/ethical AI for health: fairness/equity, interpretability, robustness, privacy (e.g., differential privacy, federated learning).
  • Track record of first-author publications in relevant venues and collaborative open-source contributions.

Department Contact for Questions - Professor Jiang Bian via email at: bianj@regenstrief.org

Additional Qualifications

Special Instructions

Priority Application Review Deadline

Expected Start Date

Posting Number - IUSM-02286-2025

Supplemental Questions

Required fields are indicated with an asterisk (*).

  • * How did you hear about this position?
    • Personal Contact: At Professional Meeting or Conference
    • Personal Contact: Direct Contact by Search Committee
    • Personal Contact: Referred by colleague or advisor
    • Personal Contact: School of Medicine recruiter
    • Personal Contact: IUHP Physician Recruiter
    • Announcement: Other Journal or Magazine
    • Announcement: Other Website
  • * Are you a dual career partner (your partner or spouse is already being recruited)?
    • Yes
    • No

Applicant Documents

Required Documents

  • Curriculum Vitae
  • Letter of Application
  • List Of References

Optional Documents

Apply