Postdoctoral Research Fellow

Details

Title Postdoctoral Research Fellow

School Harvard School of Dental Medicine

Department/Area Oral Medicine, Infection and Immunity

Position 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 Postdoctoral Research Fellow in applied data science, machine learning, and microbiology.

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.

Key responsibilities include:

• Building common data models, data dictionaries, and reproducible pipelines that harmonize clinical, demographic, microbiome, and immunological data

• Developing machine learning models (e.g., for clustering, prognostic and causal treatment effect estimation tasks)

• Drafting manuscripts, presenting at scientific meetings, maintaining a publicly available codebase

• Contributing to future grant applications

The position offers mentored training toward an independent academic career at the intersection of oral health and applied data science, including opportunities for first author publications, presentations at national and international meetings, access to the Harvard Medical School high-performance computing cluster, and support in applying for individual fellowships and career development awards.

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:

• Research doctorate (PhD, ScD, DMSc, or equivalent) with a concentration in data science, computer science, biomedical informatics, biostatistics, epidemiology, bioinformatics, computational biology, or a related field. Candidates with doctoral degrees with concentration in other fields may be considered if they demonstrate sufficient computational or microbiological expertise.

• Proficiency in Python and R for the 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:

• Machine learning applied to clinical or biomedical data, with a record of peer reviewed publications (first author preferred).

• Microbiome (16S rRNA or shotgun metagenomic) or immunological assay data.

• Experience with Git, SQL , and shared high-performance research computing environment workflows (e.g., SLURM ).

• Knowledge of periodontology or dental research; a dental degree (e.g., DMD ) is welcome but not required.

• A clear interest in an academic research career, including plans to compete for independent fellowship or career development funding.

Special Instructions

Interested candidates should submit a curriculum vitae and a cover letter describing their research experience, technical skills, and career goals. 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.

Contact Information

Sophie Spengler

Harvard School of Dental Medicine

188 Longwood Avenue

Boston, MA 02115

Contact Email [email protected]

Salary Range

This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines-policies.

Minimum Number of References Required

Maximum Number of References Allowed

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 (https://pa-hrsuite-production.s3.amazonaws.com/606/docs/1678254.pdf) 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 (https://pa-hrsuite-production.s3.amazonaws.com/606/docs/1674140.pdf) . 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