Research Associate

Research AssociateTitle - Research AssociateSchool - Harvard School of Dental MedicineDepartment/Area - Oral Medicine, Infection, and ImmunityPosition Description - The Feres Lab, located within the Department of Oral Medicine, Infection, and Immunity at the Harvard School of Dental Medicine (HSDM), is seeking a highly motivated Research Associate with strong data engineering and machine learning skills. The role is well suited to an early career data professional interested in biomedical research or to an experienced data engineer or data scientist looking for a senior technical role in an academic environment. Under the supervision of the principal investigator, the selected candidate will work within a multidisciplinary team of dentists, microbiologists, and data scientists at the Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, and the Core for Computational Biomedicine, Department of Biomedical Informatics, Blavatnik Institute, Harvard Medical School. The Research Associate will serve as the technical lead for the team's research data infrastructure.Key responsibilities include:Designing, building, and maintaining reproducible pipelines that harmonize clinical, demographic, microbiome, and immunological data into a common data modelMaintaining data dictionaries, version control, and automated data quality checks, with secure data storage and access in compliance with institutional policiesImplementing, training, and evaluating machine learning modelsPreparing analytic code, models, and documentation for public releaseContributing to manuscripts, figures, and grant applicationsThe position offers coauthorship on project publications, access to the Harvard Medical School high-performance computing cluster, and Harvard's professional development resources. This is an annual term appointment, reviewed each academic year on or before June 30th, with the possibility of extension depending on work performance, business needs, and continued funding.Basic Qualifications - The following are basic qualifications for applicants:Master's degree in data science, computer science, data engineering, biostatistics, bioinformatics, health informatics, or a related quantitative field and at least 2 years of relevant experience, or a bachelor's degree in one of these fields and at least 4 years of relevant experience in data engineering, data science, or research computing.A doctoral degree in a related field may substitute for experience.Proficiency in Python or R, and in SQL, for the processing and analysis of research data.Excellent written and spoken communication in English and the ability to work across clinical and computational teams.Additional Qualifications - Applicants with the following experience are preferred:Building data pipelines (ETL or ELT) and relational databases for research or health data, including the integration of datasets from multiple sources.Machine learning applied to clinical or biomedical data, including model validation and evaluation.Experience with Git, containers, and shared high-performance research computing (e.g., SLURM) or cloud environments.Experience with microbiome (16S rRNA and/or shotgun metagenomic), immunological assay, or clinical trial data.Strong documentation habits and attention to detail.Industry experience is welcome; candidates from technology, health care, or life sciences are encouraged to apply.Special Instructions - Interested candidates should submit a curriculum vitae or résumé and a cover letter describing their technical experience and skills. Links to code repositories (e.g., GitHub) or examples of relevant work may be included in the cover letter. Candidates will be asked to provide contact information for three references.Salary Range - $60,000-$80,000