Technical Editor and Biomedical Data Analyst

Posting Description

TECHNICAL EDITOR AND BIOMEDICAL DATA ANALYST, The Lab for Computational Physiology (LCP) - Medical Engineering and Science (IMES), to join the PhysioNet team. PhysioNet is an internationally recognized platform offering free access to a vast range of biomedical datasets and associated tools for researchers worldwide. This role primarily involves reviewing, curating, and managing datasets submitted to PhysioNet, ensuring contributions meet rigorous standards for scientific merit, reusability, and impact. Will provide feedback to data contributors and help guide their datasets to publication readiness and manage resources and metadata to maintain quality and organization of PhysioNet resources to adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principle. 

The full job description is available, here: https://acrobat.adobe.com/id/urn:aaid:sc:va6c2:92d418c9-9fe8-4cfa-8bb7-ad79af719ca9

Job Requirements

REQUIRED: Bachelor's degree in biomedical engineering, data science, computer science, healthcare informatics, or a related technical field; a minimum of one year of relevant experience in analyzing and modeling data sets and creating informative reports and dashboards; experience working with datasets, e.g. expertise in biomedical research, signal processing, and/or data analysis; proficiency in software tools such as Python or MATLAB for data manipulation, analysis, and visualization; ability to provide clear, constructive feedback to researchers and data contributors; and excellent organizational and communication skills, with the ability to manage multiple projects and deadlines. PREFERRED: Master’s degree in biomedical engineering, data science, computer science, healthcare informatics, or a related technical field; experience or familiarity with scientific research; experience with collaborative platforms like GitHub, GitLab, or similar tools; computational and data science skills; and proficiency in statistical programming languages, database query languages, predictive analysis techniques, and statistical methodology strongly.

4/29/2026