Asst Prof Machine Learning
Location: On-Site, Baltimore, MD

Job Description:

Department: Diagnostic Radiology and Nuclear Medicine
Institution: University of Maryland School of Medicine

The Imaging Computing Laboratory invites applications for a non-tenure track Assistant Professor specializing in Machine Learning for Medical Image Processing. Join a dynamic team advancing the frontiers of artificial intelligence and medical imaging to transform healthcare.


About the Role:

As a key contributor, you’ll focus on groundbreaking research in:

  • Deep Learning-based MRI Reconstruction: Enhance image quality and accelerate acquisition times.
  • Arterial Spin Labeling Perfusion MRI Processing: Innovate methods for cerebral blood flow measurement.
  • Resting-State fMRI Processing: Develop advanced techniques to understand brain connectivity and function.

This role offers the opportunity to publish impactful research, mentor future innovators, and collaborate with clinical and technical experts.


What We're Looking For:

  • Educational Background: Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field.
  • Research Experience: 3+ years of hands-on work in deep learning, MRI technologies, and medical image processing.
  • Passion for Innovation: A drive to leverage AI for transformative healthcare applications.

Why Join Us?

  • Cutting-Edge Research: Be part of pioneering advancements in medical imaging and machine learning.
  • Collaborative Environment: Work closely with world-renowned clinicians and researchers.
  • Career Development: Opportunities for growth, publishing, and interdisciplinary collaboration.
  • Inclusive Community: We celebrate diversity and are committed to fostering an inclusive environment that values all perspectives.

How to Apply:

Submit the following to ze.wang@som.umaryland.edu:

  • Full CV
  • Cover Letter
  • Contact Information for Three Referees

Alternatively, apply via this application portal.


Key Skills:

  • Asst Prof Machine Learning