Postdoctoral Research Associate - AI, LLMs, Multimodal & Foundation Models, and Agentic AI
At a glance
Junior AI Research role at Purdue University. West Lafayette · no salary stated · we estimate $78,726–$135,750 across the United States.
Purdue University has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and test LLMs, multimodal models, biomedical foundation models and agentic AI systems
- Bring together biomedical data such as EHRs, clinical notes, imaging and omics for analysis
- Create pipelines for model pretraining, fine-tuning, retrieval-augmented generation and AI agents
- Develop AI methods for clinical prediction, phenotyping, knowledge discovery and research automation
- Lead research papers and contribute to grant proposals, open-source tools and scientific presentations
What you bring
- A Ph.D. or equivalent in a relevant discipline, such as computer science, biomedical informatics or another listed field
- Research experience in at least one listed area, such as LLMs, foundation models, agentic AI or biomedical AI
- Strong Python ability and experience using PyTorch, TensorFlow or a related deep-learning framework
- Experience with large biomedical or healthcare datasets and a record of scholarly research outputs
Who this fits
This postdoctoral role suits someone seeking further research training who can lead projects independently and work with multidisciplinary teams. You’ll collaborate across Purdue, Indiana University and Regenstrief Institute, with the appointment involving Purdue’s Indianapolis campus and Indiana University School of Medicine.
From the employer
FLSA Status
ExemptJob Summary
A Postdoctoral Research Associate position is immediately available as a co-hire between the Department of Pharmacy Practice, Purdue University College of Pharmacy (Indianapolis campus), and the Department of Biostatistics and Health Data Science, Indiana University School of Medicine. The fellow will work in a highly collaborative environment with Purdue, Indiana University, and Regenstrief Institute investigators to develop and apply advanced AI methods for biomedical discovery, clinical research, and precision health.
This position is ideal for candidates seeking advanced training and leadership opportunities at the intersection of artificial intelligence, large language models (LLMs), multimodal biomedical data, foundation models, agentic AI and AI agent development, and translational health data science.
Research Areas: The postdoctoral fellow will contribute to projects in one or more of the following areas:
• Large language models and generative AI for biomedical and clinical applications
• Biomedical and clinical foundation models, including pretraining, adaptation, and evaluation
• Multimodal AI integrating structured EHR data, clinical text, imaging, omics, and other biomedical data
• Representation learning, self-supervised learning, and transfer learning for health data
• Agentic AI and AI agent development for clinical and biomedical research, including tool use, reasoning, planning, memory, orchestration, and multi-agent workflows
• Biomedical knowledge graphs, retrieval-augmented generation, and knowledge-enhanced AI
Primary Responsibilities: The Postdoctoral Research Associate is expected to lead and contribute to independent and collaborative research projects, including but not limited to:
• Developing and evaluating LLMs, multimodal AI models, biomedical foundation models, and agentic AI systems
• Integrating and analyzing large-scale multimodal biomedical datasets, including EHRs, clinical text, imaging, omics, medication, and other real-world health data
• Designing pretraining, fine-tuning, instruction-tuning, RAG, multimodal learning, and AI-agent development pipelines
• Developing AI-enabled methods for clinical phenotyping, prediction, knowledge discovery, precision therapeutics, and intelligent research automation
• Leading manuscript preparation and contributing to grant proposals, open-source tools, and scientific dissemination
• Collaborating with multidisciplinary teams across clinical, biomedical, informatics, and AI research
Core Qualifications
1. Ph.D. or equivalent degree in a related field, such as computer science, artificial intelligence, biomedical informatics, health data science, computational biology, biomedical engineering, biostatistics, or a related discipline
2. Demonstrated research experience in one or more of the following areas: LLMs; generative AI; agentic AI or AI agent development; foundation models; multimodal learning; NLP; deep learning; self-supervised learning; representation learning; or biomedical AI
3. Strong programming skills in Python and experience with modern deep-learning frameworks such as PyTorch, TensorFlow, or related tools
4. Experience working with large-scale biomedical or healthcare datasets; experience with EHR, clinical text, imaging, omics, knowledge graphs, or other multimodal data is highly desirable
5. Strong written and oral communication skills, with evidence of scholarly productivity, including peer-reviewed publications, conference papers, or equivalent research outputs
6. Ability to work effectively in multidisciplinary teams and independently drive innovative AI research projects
Application Materials
1. Curriculum Vitae
2. Cover letter describing research interests, relevant AI/LLM/agentic AI experience, and career goals
3. Contact information for 3-4 references
Contact
Serena Guo, MD, PhD (serena.guo@purdue.edu) Yi Zhao, PhD (yz125@iu.edu)
Purdue University is an equal opportunity/equal access university.