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Indiana University Bloomington

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Postdoctoral Fellow in Biostatistics & Health Data Science (LLMs for Clinical Data Harmonization) Indiana University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Competitive salary and benefits through Indiana University.

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Country

United States

University

Indiana University Bloomington

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Keywords

Computer Science
Data Science
Biomedical Engineering
Information Technology
Biostatistics
Artificial Intelligence
Natural Language Processing
Medical Science
Data Harmonization
Statistics
Large Language Models
ML

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About this position

Indiana University is recruiting a Postdoctoral Fellow in Biostatistics & Health Data Science at the IU School of Medicine Indianapolis, in collaboration with the Regenstrief Institute.

This postdoctoral opening focuses on large language models (LLMs), intelligent agents, clinical data harmonization, semantic normalization, ontology alignment, and health data interoperability. The research aims to support transparent, scalable, and auditable mapping of real-world health data to standards such as OMOP CDM, FHIR, and UMLS.

The role is ideal for candidates interested in applied AI for healthcare, including machine learning, deep learning, natural language processing, retrieval-augmented generation (RAG), schema matching, terminology mapping, and hybrid reasoning systems that combine knowledge-grounded methods with flexible ML.

The fellow will work with messy multi-source clinical and public health data, contribute to open-source tooling and reproducible pipelines, and help develop methods that can be deployed in real-world health data operations. The environment includes collaborations across academic, clinical, and public health settings, with opportunities to publish and contribute to grant development.

Eligibility highlights: Ph.D. by start date in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related field; strong ML/deep learning background; experience with healthcare data (EHR, clinical text, imaging, or omics); Python, PyTorch/scikit-learn, Git, and experiment tracking tools.

Funding: competitive salary and benefits through Indiana University.

Application: review the posting and apply via the Indiana University PeopleAdmin portal. The search continues until the position is filled.

Funding details

Competitive salary and benefits through Indiana University.

What's required

Ph.D. by the start date in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area. Strong foundation in machine learning/deep learning and expertise in at least one of multimodal learning, time-series modeling, or NLP. Demonstrated experience with healthcare data such as EHR, clinical text, imaging, or omics. Proficiency in Python and ML tooling such as PyTorch and scikit-learn, version control with Git, and experiment tracking tools such as Weights & Biases. Excellent written and oral communication skills and ability to collaborate with multidisciplinary teams. Preferred: experience with concept normalization, ontology mapping, schema alignment, LLM agents, tool-augmented reasoning, hybrid rules + LLM systems, publications in informatics/ML/AI/knowledge representation, and multi-site or federated data harmonization.

How to apply

Apply through the Indiana University PeopleAdmin posting. Use the application portal linked in the post and direct questions to Professor Jiang Bian by email.

More information can be found here

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