Graduate Research Assistant
About The Position
We are seeking a graduate research assistant to support an integrated experimental-computational project focused on understanding how aortic stents and endovascular grafts alter arterial stiffness, wave reflections, and left ventricular afterload. The project combines in vitro flow-loop experiments with computational fluid dynamics (CFD) and, where appropriate, fluid-structure interaction (FSI) simulations to quantify the hemodynamic consequences of local stiffening following EVAR/TEVAR and aortic coarctation repair. This position is ideal for a Master's or PhD student interested in cardiovascular biomechanics, translational research, and device design. You will collaborate closely with cardiac surgeons, postdoctoral researchers, and computational scientists to translate clinical questions into validated experimental setups and computational models, contributing directly to publications and translational research initiatives.
Requirements
- Demonstrated proficiency in Python or MATLAB for data analysis, and visualization.
- Prior hands-on laboratory experience (e.g., benchtop experiments, fluid circuits, electronics, or mechanical testing).
- Strong organizational skills and attention to detail in managing experiments and datasets.
- Familiarity with cardiovascular physiology and basic hemodynamics (e.g., pressure-flow relationships, wave propagation).
Nice To Haves
- Experience with 3D modeling and meshing (e.g., Blender, 3D Slicer, Mimics, Gmsh, or similar).
- Exposure to CFD/FSI tools such as ANSYS Fluent, OpenFOAM, or SimVascular.
- Prior experience with flow-loop setups, pumps, compliance chambers, or pressure/flow sensors.
- Comfort working with medical imaging data (CT/MR/CTA) and basic image processing workflows.
- Any prior experience with digital image correlation (DIC) or optical strain measurement is a plus.
Benefits
- The opportunity to work in a Harvard-affiliated, translational research environment at the interface of engineering and cardiovascular surgery.
- Direct experience in both in vitro experimentation and computational modeling, highly valuable for future careers in academia, medicine, or industry R D.
- Opportunities to contribute to abstracts, manuscripts, and conference presentations, with strong potential for co-authorship.
- Close mentorship from surgeons, postdoctoral researchers, and computational scientists, with regular feedback and guidance tailored to your graduate training goals.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Number of Employees
5,001-10,000 employees
