HMS - Research Associate in Biomedical Informatics (Patel Lab)

The Protocol Labs Network is an ecosystem of teams pushing the boundaries of decentralized technologies, research, and open-source innovation. Explore opportunities across the network and join the mission. HMS - Research Associate in Biomedical Informatics (Patel Lab) Title HMS - Research Associate in Biomedical Informatics (Patel Lab) School Harvard Medical School Department/Area Biomedical Informatics Position Description 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 geneby‑exposome interactions and therapeutic discovery. Seeking an individual with a PhD to conduct research in the area of biomedical informatics, multi‑omic integration analytics and machine learning. In this role you will produce highly impactful biomedical informatics research that presents new innovations in methods and novel findings that inform disease etiology. The exposome is a promising and emerging modality to explain disease variation (papers in press in *Nature Medicine*) that impacts humans on all levels: from the single cell to populations, providing a rich substrate to do novel work. Candidates with experience in developing approaches to research and analyze large multi‑modal datasets and who wish to deploy the next generation of exposome AI models are highly encouraged to apply. This position comes with data ready to analyze, and you can focus on developing research findings and writing papers from day 1. Responsibilities include: 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 at 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. Basic Qualifications PhD in Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or related field. Additional Qualifications 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, multiomics integration, and exposure‑wide association studies (ExWAS) and GIS preferred. Special Instructions Statement of Research for PhD work Cover Letter describing your interest in the lab and initial ideas for new research directions or projects you could undertake in the lab. Note with names and contact information for three people who have agreed to serve as your reference Please submit application documents through the ARIeS portal. Selected candidates will be invited for in‑person interviews involving a research presentation on past work. Expected Dates Duration: This is a one‑year term position from the date of hire, with the possibility of extension, contingent upon work performance, business need, and continued funding to support the position. Contact Information Nichole Parker 10 Shattuck St Boston, MA 02115 Contact Email Salary Range $90K-$120K Minimum Number of References Required 3 Maximum Number of References Allowed 3 Keywords EEO/Non‑Discrimination Commitment Statement Harvard University is committed to equal opportunity and non‑discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non‑discrimination policy. Harvard’s equal employment opportunity policy and non‑discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination. Supplemental Questions Required fields are indicated with an asterisk (*). #J-18808-Ljbffr Kubelt