Postdoctoral Fellow in Biostatistics and Health Data Science jobs in United States
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Indiana University School of Education · 1 month ago

Postdoctoral Fellow in Biostatistics and Health Data Science

Kinsey Institute is seeking a Postdoctoral Researcher to advance research at the intersection of artificial intelligence for healthcare and multimodal data analysis. The successful candidate will collaborate with an interdisciplinary team to develop methods that improve patient outcomes and health system operations, focusing on causal AI and multimodal learning.

Higher Education

Responsibilities

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

Qualification

Machine LearningDeep LearningMultimodal LearningHealthcare Data ExperiencePythonNatural Language ProcessingCausal MethodsData EngineeringMLOpsEthical AI KnowledgePublication Track RecordCommunicationCollaboration Skills

Required

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

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

Company

Indiana University School of Education

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The Indiana University School of Education is known for preparing reflective, caring, and skilled educators who make a difference in the lives of their students in Indiana, throughout the United States, and around the world.

Funding

Current Stage
Growth Stage
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