Axle - Data Scientist, Medical Imaging
Requirements
• Master's degree or PhD in biomedical engineering, computer science, data science, medical physics, electrical engineering, or a related quantitative field, or a Bachelor's degree with equivalent experience. • Three or more years of hands-on experience in medical image analysis, in research or industry. • Strong Python skills, including scientific computing and deep learning libraries, with a habit of writing tested, maintainable code. • Familiarity with DICOM, NIfTI, and other medical image formats. • Experience applying AI to medical images across segmentation, classification, and embeddings. • Experience with traditional image analysis algorithms for registration, feature extraction, and machine learning. • Experience evaluating models rigorously on imaging data, with sound validation design and appropriate performance metrics. • Experience working with clinical imaging data and its privacy requirements. • Comfort working in Linux environments with version control and containers. • Collaboration & Communication: Ability to work effectively in a highly interdisciplinary environment with clinicians, imaging scientists, biologists, and software engineers, and to explain complex technical concepts clearly to people in other disciplines. • Experience with Nextflow or similar workflow orchestration tools on clusters or cloud platforms. • Experience with EHR data, clinical data models such as OMOP or FHIR, and standa • clinical vocabularies. • Familiarity with the OMOP medical imaging extension, or with imaging data in research data warehouses. • Experience with multimodal models that combine imaging with EHR data or clinical text, including medical foundation models. • Experience with microscopy or digital pathology image analysis. • Experience with SQL and relational or analytical databases. • Track record of publications, conference presentations, or open-source contributions in medical imaging or machine learning. • Experience working with NIH or other federal health and biomedical research organizations. • Disclaimer: The above description is meant to illustrate the general nature of work and • level of effort being performed by individuals assigned to this position or job description. This is not • restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals • may be required to perform duties outside of their position, job description or responsibilities as needed. • Disclaimer: • The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity • in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, • gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, • status with respect to public assistance, and other characteristics protected under state, federal, or local law • and to deter those who aid, abet, or induce discrimination or coerce others to discriminate. • Accessibility: If you need an accommodation as part of the employment process please contact: [email protected]
Responsibilities
• Medical Image Processing: Build and maintain Python pipelines that prepare large, varied medical imaging collections for analysis, with attention to metadata quality and the inconsistencies found in real clinical data. • AI for Medical Imaging: Develop, apply, and evaluate AI models for segmentation, classification, and image embeddings. Judge model quality and decide when a model needs retraining or a different approach. • Traditional Image Analysis: Apply established image analysis methods for registration, normalization, and feature extraction, and combine them with machine learning where they fit the problem. • Machine Learning and Multimodal Modeling: Build and evaluate models that combine imaging with clinical data and reports, using sound validation practices. • Clinical Data Integration: Work with clinical data models and standard vocabularies to connect imaging results with patient records, cohorts, and outcomes. • Reproducible, Scalable Workflows: Run pipelines with workflow orchestration, containers, and cluster or cloud computing. Keep code tested and documented so others can rerun the work. • Collaboration and Communication: Work closely with clinicians, imaging scientists, and software engineers to define questions and interpret results. Present findings clearly, and contribute to publications, conference presentations, and open-source tools.
Benefits
• 100% Medical, Dental & Vision Coverage for Employees • Paid Time Off and Paid Holidays • 401K match up to 5% • Educational Benefits for Career Growth • Employee Referral Bonus • Healthcare (FSA) • Parking Reimbursement Account (PRK) • Dependent Care Assistant Program (DCAP) • Transportation Reimbursement Account (TRN)
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