Postdoctoral Fellow in Biomedical Informatics (Cai Lab)

Harvard University

Cambridge, MA

JOB DETAILS
SKILLS
Biomedicine, Biostatistics, Clinical Information Systems, Communication Skills, Computer Science, Computer Security, Cross-Functional, Data Sets, Deep Learning, Drug Discovery, Equal Employment Opportunity (EEO), Informatics, Machine Learning, Medical Record System, Modeling Languages, Neural Networks, Presentation/Verbal Skills, Python Programming/Scripting Language, Quantitative Research, R Programming Language, Statistics, Writing Skills
LOCATION
Cambridge, MA
POSTED
30+ days ago

Position Details

Title: Postdoctoral Fellow in Biomedical Informatics Cai Lab School: Harvard Medical School Department/Area: Biomedical Informatics

Position Description

A Postdoctoral Research Fellow position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic research group focused on several synergistic goals:

• Generating actionable Real-World Evidence (RWE) from multi-institutional Electronic Health Records (EHR) • Improving the generalizability of clinical evidence across diverse populations using multi-source and multi-modal data • Accelerating drug discovery by leveraging these rich integrated datasets

This role offers a unique opportunity to develop methodological innovations that bridge the gap between computational theory and impactful clinical application.

We are seeking a highly motivated individual with a strong statistical and machine learning background. The ideal candidate will have existing expertise in several of the following areas aligned with our research focus:

• Causal inference • Invariant learning and representation learning • Distributionally robust optimization • Graph Neural Networks • Large Language Models (LLMs) and geometric deep learning • Federated learning and privacy preserving computing

Basic Qualifications

Candidates must hold a Ph.D. in a quantitative field such as statistics, biostatistics, computer science, or a related discipline. Success in this position requires strong quantitative research capabilities and demonstrated proficiency in programming specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must possess excellent written and oral communication abilities to effectively disseminate research findings and collaborate within a multidisciplinary team.

Additional Qualifications

Special Instructions

Contact Information

Mo Moro Contact Email: mohammed_morohms.harvard.edu

Salary Range Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at http://postdoc.hms.harvard.edu/guidelines

Minimum Number of References Required Maximum Number of References Allowed

Keywords

EEONon-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 strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvards 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 universitys non-discrimination policy. Harvards 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.

Applicant Documents

Required Documents

• Curriculum Vitae • Cover Letter • Statement of Research • List of References • Optional Documents

About the Company

H

Harvard University