Postdoc – Computational Medical Imaging & Hyperthermia

University of Maryland, Baltimore; Baltimore (MD); On-site; USD 52,000 - 76,000; Full time

Job summary

University of Maryland, Baltimore invites applications for a Post Doctoral Fellow in the Department of Radiation Oncology. The successful candidate will develop high‑resolution, patient‑specific head models from CT/MRI for electromagnetic and bioheat simulations, using advanced segmentation tools and mesh optimization.

The role includes collaboration with clinicians and industry partners and exposure to clinical workflows.

Qualifications

• PhD in medical physics or related field.
• At least 1 year of research in medical-image segmentation and 3D modelling.
• Experience with CT/MRI datasets.

Responsibilities

• Develop high-resolution virtual models of the head from CT/MRI datasets.
• Perform tissue segmentation (manual, semi-automatic, automatic).
• Integrate segmentation algorithms into reproducible workflows.
• Refine geometries and optimize mesh generation for accuracy and efficiency.
• Develop multiphysics models coupling EM fields with bioheat transfer.
• Conduct mesh-convergence and sensitivity analyses.
• Compare predictions with experimental measurements.
• Prepare manuscripts and conference materials.
• Collaborate with physicists, engineers, and clinicians.
• Shadow clinical hyperthermia treatments to understand constraints.

Skills

Medical image segmentation

3D anatomical modelling

CT/MRI processing

Python

MATLAB

Education

PhD in medical physics

Tools

Synopsys Simpleware

COMSOL Multiphysics

ANSYS

GPU computing

Job description

University of Maryland, Baltimore invites applications for a Post Doctoral Fellow in the Department of Radiation Oncology. The successful candidate will develop high‑resolution, patient‑specific head models from CT/MRI for electromagnetic and bioheat simulations, using advanced segmentation tools and mesh optimization.

The role includes collaboration with clinicians and industry partners and exposure to clinical workflows.