HMS - Research Associate in Biomedical Informatics; Patel Lab

HMS - Research Associate in Biomedical Informatics (Patel Lab)

School:
Harvard Medical School

Department:
Biomedical Informatics

Position:
Chirag Patel’s group in the Department of Biomedical Informatics, Harvard Medical School, is seeking a Research Associate with a focus in Biomedical Informatics for gene‑by‑exposome interactions and therapeutic discovery. The role requires a PhD and involves conducting research in biomedical informatics, multi‑omic integration analytics, and machine learning. You will produce highly impactful research, presenting new innovations in methods and novel findings that inform disease etiology.

The exposome is an emerging modality that explains disease variation and impacts humans from single cell to population levels. Candidates with experience in developing approaches to analyze large multi‑modal datasets and deploying next‑generation exposome AI models are encouraged to apply. This position comes with data ready to analyze, allowing you to focus on developing research findings and writing papers from day one.

• Research and translate exposome data science into real‑world clinical applications.
• Independently research and design exposome foundation models for disease physiology.
• Characterize how an individual’s exposome drives variation in response to pharmaceutical intervention.
• Collaborate with interdisciplinary teams across Harvard (HSPH, HMS) and partner universities to enhance data collection, cleaning, and integration processes, ensuring data accuracy and consistency.
• Produce high‑impact peer‑reviewed articles and presentations for academic and non‑academic audiences.

• PhD in Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field.

• Demonstrated expertise in large‑scale analysis and familiarity with health‑related datasets.
• Proficiency in statistical software (R, Python, etc.) and working knowledge of data management protocols.
• Experience with exposome or environmental data, multi‑omics integration, and exposure‑wide association studies (ExWAS) and GIS preferred.

$90 K – $120 K

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