Postdoc: Digital Twin AI for Biofluid Dynamics & Robotics

Johns Hopkins University; Baltimore (MD); On-site; USD 63,000 - 100,000; Full time

Job summary

Johns Hopkins University in Baltimore seeks a Postdoctoral Research Fellow to advance a state-of-the-art digital twin in biofluid dynamics, combining Physical AI, high-fidelity CFD, and biomedical robotics. The role develops virtual testbeds for endovascular platforms and neurosurgery training.

You will work on two pillars: CFD for blood flow simulation and biomechanical simulation of device-tissue interaction, with emphasis on GPU-accelerated FSI and multi-physics coupling across asynchronous

Qualifications

• PhD in Mechanical Engineering, Biomedical Engineering, Engineering Mechanics, or closely related field.
• Demonstrated expertise in CFD and FSI modeling.
• Strong HPC background including GPU-native solver development (CUDA) and parallel computing.

Responsibilities

• Develop GPU-native, sharp-interface immersed boundary CFD framework for near-real-time, multi-GPU simulations of device-flow-clot-wall interactions.
• Bridge hemodynamics and tissue mechanics by implementing a lightweight coupling interface between asynchronous solvers.

Skills

CFD

FSI

HPC

CUDA

Education

PhD in Mechanical Engineering or related field

Job description

Johns Hopkins University in Baltimore seeks a Postdoctoral Research Fellow to advance a state-of-the-art digital twin in biofluid dynamics, combining Physical AI, high-fidelity CFD, and biomedical robotics. The role develops virtual testbeds for endovascular platforms and neurosurgery training.

You will work on two pillars: CFD for blood flow simulation and biomechanical simulation of device-tissue interaction, with emphasis on GPU-accelerated FSI and multi-physics coupling across asynchronous