HOPPR is building the first multimodal AI foundation model for medical imaging.
Research Intern
Location
United States
Posted
21 hours ago
Salary
$20 - $30 / hour
Seniority
Entry Level
Job Description
Research Intern
HOPPR
• Assist in the curation of medical imaging and clinical report data and the development of AI-powered analysis pipelines based on machine learning and data science principles. • Organize, clean, and curate medical imaging datasets with associated radiology reports to ensure data quality and consistency for downstream analysis. • Conduct exploratory data analysis and create visualizations to identify patterns, trends, and anomalies in imaging and clinical datasets. • Perform quality assurance checks on processed data and analysis outputs to validate accuracy and reliability. • Support the implementation of machine learning models such as image-based classification, segmentation, and natural language processing of clinical reports. • Document code, workflows, analysis methodologies, and results to ensure reproducibility and knowledge transfer. • Collaborate cross-functionally with other teams to understand clinical context and refine analysis approaches. • Participate in regular team meetings and present findings through written summaries and oral presentations.
Job Requirements
- Currently enrolled in a degree-granting program in Computer Science, Biomedical Engineering, Data Science, Statistics, or a related technical field.
- Proficiency in Python programming and familiarity with data science and ML libraries (pandas, NumPy, scikit-learn, PyTorch).
- Exposure to SQL is a plus.
- Experience or strong interest in medical imaging, computer vision, and/or natural language processing.
- Strong quantitative analytical abilities and curiosity about healthcare applications.
- Excellent written and verbal communication skills, with the ability to present complex information clearly and concisely.
- High level of accuracy and attention to detail.
- Strong problem-solving skills and the ability to think critically.
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