Postdoctoral Research Associate - Radiology

Position Summary

We are considering the applications of a postdoctoral research fellow in neuroimaging, artificial intelligence (AI), and statistical genomics. This career‑building position is within the Department of Radiology, ranking second highest NIH‑funded among the Radiology Departments in the US.

The position will work in the Neuroimaging Informatics and Artificial Intelligence (NeuroAI) Lab under Dr. Ganesh Chand, Assistant Professor of Radiology at WashU Medicine, a top‑ranked medical school. The candidate will work on identifying multimodal biomarkers, leveraging MRI, PET, fMRI, EEG, behavior, genetics, and proteomics using advanced quantitative modeling techniques and AI methodologies in brain diseases. Responsibilities include developing new algorithms, testing, validation, and application across these modalities.

Opportunity to work on big data studies in health and diseases, including Alzheimer’s disease and other conditions such as schizophrenia, psychosis, autism, etc. Collaboration with major research universities worldwide and neuro‑related industries is expected.

• Perform quality checks of brain PET/MRI cognitive, clinical, genetic, and proteomic data and manage them in the data repository and computer servers.
• Run existing PET/MR brain image processing pipelines on the computer servers, produce the results, and communicate with the group members.
• Write computer codes for the above data modalities under the guidance of the team leader.
• Engage in the development and testing/validation of new quantitative AI algorithms and their applications to PET, MRI, EEG, behavioral, clinical, genetic, and proteomic data.
• Prepare documentation of existing and newly developed brain image analysis pipelines, algorithms, and quantitative methods.
• Assist the team in the manuscript preparation of the research findings.
• Support the team leader to fulfill the research objectives of their funded projects.
• Assist the team leader in generating preliminary results for grant funding proposals.
• Publish research findings in reputable scientific journals.
• Present research at conferences and contribute to grant applications.
• Mentor junior team members.
• Contribute to the overall research goals and objectives of the team.

This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and provide standard care to research animals.

Base pay is commensurate with experience.

• Ph.D., M.D., or equivalent terminal or doctoral degree.
• No specific certification or professional license required.
• No specific work experience required.
• Driver’s license not required.

• Ph.D. in a quantitative field such as biomedical physics, engineering, computer science, data science, bioinformatics, computational biology, computational neuroscience, statistical genomics, applied mathematics, biostatistics, or a related field.
• Strong computer skills (knowledge of Python, R, Python libraries, MATLAB, statistical analysis packages, basic shell scripting, experience in Unix/Linux platform) and experience with deep learning tools (e.g., PyTorch, Tensor Flow, Keras), neuroimaging analysis tools (e.g., PMOD, SPM, FSL) and statistical genetics (GWAS, PRS, etc.) and related tools (e.g., PLINK).
• Experience with either 3D image processing (e.g., brain PET and MRI analysis) or statistical genomics (GWAS, PRS calculation, etc.) is highly preferred.
• Experience with multi‑omics data analysis.
• Experience with neuroimaging‑behavior and/or neuroimaging‑genetics analysis.
• This position is ideal for a candidate who is familiar with emerging AI techniques, neuroimaging methods, and statistical genetics research.
• Strong communication (writing and speaking) and ability to collaborate in teamwork.

Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full‑time equivalent (FTE) workload, and weekly standard hours. For a summary of benefits, visit (Use the "Apply for this Job" box below)..

Washington University in St. Louis is committed to the principles and practices of equal employment opportunity. It is the University’s policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, citizenship (where prohibited by federal law), age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information.