OPS Biology-Focused Machine Learning Assistant

The OPS research assistant will support multiple ongoing research initiatives within the laboratory, contributing to the development and application of advanced computational methodologies for biomedical imaging and spatial omics research. Specific duties include:

• Developing machine learning and data analysis pipelines using Python and R, leveraging frameworks such as TensorFlow and PyTorch for imaging and omics-based applications.
• Applying state-of-the-art techniques in data science and AI to analyze the cellular and molecular microenvironment in tissues from various organ systems, utilizing spatial omics and high-resolution microscopy datasets.
• Performing detection, segmentation, and quantification of anatomical features in tissue images; building predictive models of disease; integrating image and molecular omics data; and developing scalable data visualization tools.
• Ensuring data quality, standardization, and reproducibility through rigorous quality control practices and adherence to software development best practices.
• Designing and implementing interactive visualization platforms to display spatial omics and microscopy data, with attention to user interface and user experience (UI/UX) tailored for a multidisciplinary group of researchers and stakeholders.
• Participating in user feedback collection, which may include designing and conducting user experience surveys to inform tool refinement.
• Contributing to scientific communication, including writing progress reports, assisting in manuscript preparation, and presenting research findings at internal meetings or external conferences.
• Engaging in collaborative research with a multidisciplinary team at a leading academic medical center.

$18/hr

B.Sc. degree in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.

• Bachelor’s degree in a biological science, health science, or related field, or equivalent combination of education and relevant experience.
• Proficiency in digital and computational pathology, AI/ML algorithms, and data science tools.
• Experience with image analysis, computer programming (Python and R), and machine learning frameworks (TensorFlow, PyTorch).
• Familiarity with spatial omics, bioimaging data processing, and UI/UX design principles.
• Graphic design skills and the ability to develop visual identities are considered a strong asset

Application must be submitted by 11:55 p.m. (ET) of the posting end date.

This is a time-limited position.