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ML Postdoc Researcher - Healthcare AI Innovation

Job in Seattle, King County, Washington, 98127, USA
Listing for: Truveta
Full Time position
Listed on 2026-10-02
Job specializations:
  • Research/Development
    Data Scientist
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Analyst
Salary/Wage Range or Industry Benchmark: 69000 - 83000 USD Yearly USD 69000.00 83000.00 YEAR
Job Description & How to Apply Below

ML Postdoc Researcher - Healthcare AI Innovation

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture. Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote

About Truveta

Truveta is transforming healthcare by enabling researchers, clinicians, and life sciences organizations to learn from one of the most comprehensive collections of de-identified patient data in the United States. With access to longitudinal electronic health record (EHR) data from over
120 million patients(which represents over a third of the US population), we are uniquely positioned to drive breakthroughs in clinical research and improve patient outcomes.

This Opportunity

We areseekinga highly motivated

Postdoctoral Researcher to explore and develop novel applications ofcutting-edgeAI/ML technologies on large-scale real-world clinical data.

This role is designed for recent PhD graduates who are passionate about pushing the boundaries of machine learning in healthcare. You will work at the intersection ofmachine learning, clinical data, and biomedical science,identifying new opportunities where modern AI can unlock insights that were previously out of reach.

A key expectation is not just execution—butimagination: the ability to envision and prototype entirely new ways to use rich patient data to solve meaningful healthcare problems.

Who You Are
  • Curious and imaginative: You naturally think beyond existing solutions andask“what hasn’t been done yet?”
  • Impact-driven: You care about applying research to real-world healthcare problems
  • Comfortable with ambiguity: You thrive in open-ended environments where defining the problem is part of the job
  • Collaborative: You enjoy working across domains and learning from experts in different fields
What You’ll Do
  • Innovate: Identify and propose novel, high-impact applications of AI/ML using large-scale EHR data
  • Research & Prototype: Design, develop, and evaluate state-of-the-artmodels (e.g., foundation models, multimodal learning, causal ML, generative AI)
  • Work Across Modalities: Integrate structured and unstructured EHR data with emerging data types such as genomics, imaging, and clinical notes
  • Collaborate Cross-Functionally: Partner with clinicians, data scientists, and product teams to translate research ideas into real-world solutions
  • Publish & Share: Contribute to top-tier conferences/journals and represent Truveta in the research community
  • Explore the Unknown: Proactivelyidentifyproblems that have not yet been addressed and define new research directions
What We’re Looking For Basic Qualifications
  • Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
  • Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
  • Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
  • Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
  • Deliver the next generation of innovation in trustworthy healthcare.
Preferred Qualifications
  • Experience with healthcare data (EHRs, claims, clinical notes) or biomedical data (genomics, imaging)
  • Familiarity with cutting-edge areas such as:
  • Foundation models / LLMs in healthcare
  • Multimodal learning
  • Causal inference
  • Representation learning on longitudinal data
  • Track record of publications in top-tier ML or healthcare venues (e.g., NeurIPS, ICML, ICLR, MLHC, AMIA)
  • Ability to work across disciplines and communicate with both…
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