Postdoctoral Research Fellow: Fluid Dynamics, Physical AI, and Biomedical Robotics

Description

We are seeking a highly motivated and talented Postdoctoral Research Fellow to help develop a state-of-the-art digital twin in biofluid dynamics. This position lies at the intersection of Physical AI, high-fidelity computational fluid dynamics (CFD), and advanced biomedical robotics.

The successful candidate will contribute to the development of two key components of our virtual testbed:

1. Computational Fluid Dynamics for Blood Flow Simulation
2. Biomechanical Simulation of Device-Tissue Interaction

Together, these capabilities will support the high-throughput, low-latency simulation environment required for training foundation models and embodied AI systems for next-generation endovascular robotic platforms in neurosurgery.

Core Responsibilities

• Advance Fluid-Structure Interaction (FSI):
  Develop and expand our GPU-native, sharp-interface immersed boundary CFD framework to enable near-real-time, multi-GPU simulations of device-flow-clot-wall interactions under physiologically realistic pulsatile flow conditions.
• Multi-Physics Coupling:
  Bridge hemodynamics and tissue mechanics by implementing a lightweight coupling interface that supports bidirectional force exchange and geometric constraint handling between asynchronous solvers.

 

Qualifications

Required Qualificatons

• PhD in Mechanical Engineering, Biomedical Engineering, Engineering Mechanics, or a closely related field.
• Demonstrated expertise in Computational Fluid Dynamics (CFD) and Fluid-Structure Interaction (FSI) modeling.
• Strong background in High-Performance Computing (HPC), including GPU-native solver development (e.g., CUDA) and parallel computing.

 

The referenced salary range is based on Johns Hopkins University's good faith belief at the time of posting. The actual compensation offered to the selected candidate may vary and will be based on factors including, but not limited to, the experience and qualifications of the selected candidate – e.g., years in rank, training, field, discipline, other work experience, and other similar factors; geographic location; internal equity; external market conditions; and other factors as reasonably determined by the University.

 

Equal Employment Opportunity Statement

Salary Range
The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

Total Rewards
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Equal Opportunity Employer
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Pre-Employment Information
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