The Musculoskeletal Digital Innovation and Informatics (MDI²) Program in the Department of Orthopedics and Sports Medicine has an immediate opening for a motivated Research Assistant (RA). Under general supervision, the RA will contribute to several image processing and modeling projects to assist with clinical decision making in patients with musculoskeletal joint disorders.
The central theme of the work is the development of automated, end-to-end tools for comprehensive assessment of joint anatomy and function in three dimensions: reconstructing patient-specific bone models from routine clinical imaging, quantifying morphology to localize the type and extent of anatomical abnormality, simulating joint articulation across ranges of motion representative of daily and athletic activity, and interpreting the results against normative reference data. These tools are intended to run without manual intervention, at cohort scale, and to be reliable enough that clinicians can act on their output, which places a premium on methods that behave predictably across the full spectrum of anatomy encountered in practice, from normal through deformity.
Principal duties and responsibilities
- According to prescribed protocols and assigned schedules, perform a variety of image analysis studies, utilizing standard laboratory/research equipment and software, recording and checking results for completeness and accuracy, and assisting in troubleshooting procedures.
- Develop algorithms for end-to-end automatic 3D joint morphology assessment.
- Use image segmentation techniques to generate 3D models from imaging data. Conduct 2D and 3D measurements to quantify different anatomical indices of the joints. Contribute to computational simulations (e.g., finite element modeling, statistical shape modeling) and analysis of simulation outputs.
- Conduct literature searches and reviews, compiling information for journals and suggesting uses for new techniques to the PI. Attend courses, lectures, and conferences to further own knowledge of research and laboratory techniques, consulting with other researchers and technicians to exchange information.
- Coordinate research projects and manage the timing of several concurrent projects using project management skills and collaboration with staff.
- Assist in the process of data collection and analysis using varied instrumentation and software; provide proper documentation and organization to ensure integrity and organization of collected data.
- Apply basic statistical knowledge; understand, interpret, and describe complex data by preparing graphs and tables.
- Participate in the preparation, review, and submission of manuscripts and abstracts for publication.
Required skills and experience
- Master's degree in a STEM field (mechanical or biomechanical engineering is preferred).
- Minimum of one year of relevant work experience.
- Strong foundation in analytical and computational geometry and in 3D rigid-body kinematics. For example, definition and construction of coordinate systems, spatial transformations and transformation matrices, and the properties and limitations of common rotation representations, together with an understanding of why anatomically referenced frames are a prerequisite for meaningful comparison between subjects.
- Expertise with Python.
- Experience working with medical images and/or 3D geometric data (e.g., volumetric images, surface meshes, point clouds).
Desired skills and experience
- Experience developing algorithms that perform reliably across a wide range of normal and pathological anatomies.
- Computer simulation of joint motion or multibody kinematics; finite element analysis.
- Basic knowledge of human musculoskeletal anatomy, biomechanics, and pathology.
- Sound software practice (e.g., version control, testing, reproducible pipelines) and experience processing data at scale (e.g., batch or high-performance computing).
- Statistical methods for measurement validation and reliability.
- Registration and correspondence methods (e.g., rigid and non-rigid registration, statistical shape modeling, landmark propagation).
- Experience with generative AI and large vision models.
- Experience generating 3D anatomical models from medical images (e.g., segmentation, surface and mesh processing).
How to apply
Apply online through the Boston Children's Hospital careers site.