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University of Maryland, Baltimore
Baltimore, Maryland, United States
(on-site)
Posted
21 hours ago
University of Maryland, Baltimore
Baltimore, Maryland, United States
(on-site)
Asst Prof Machine Learning
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Asst Prof Machine Learning
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description
Job DescriptionThe Imaging Computing Laboratory at the Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine is looking for a candidate to fill an Assistant Professor position in machine learning based medical image processing. This position is in the non-tenure track. The research focuses will include: deep learning-based MRI image reconstruction, deep learning based arterial spin labeling perfusion MRI processing, and resting state fMRI processing. Ideal candidates should have a PhD in computer science, biomedical engineering, or electrical engineering. Over three years of research experience in deep learning, MRI and medical image processing is preferred.
Candidates should submit a full CV, a cover letter, and names of three referees who can provide recommendation letters to [email protected]
Qualifications
For immediate consideration, please send a cover letter and a recent CV, including names and contact information of three references to the following link:
https://umb.taleo.net/careersection/jobdetail.ftl?job=240000I7&lang=en
UMB is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy.
We value diversity and how it enriches our academic and scientific community and strive toward cultivating an inclusive environment that supports all employees.
Job ID: 80122350
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