1,057 engineering-computation-"https:"-"https:"-"https:"-"https:"-"Univ"-"UNIV" positions at Stony Brook University
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education and relevant experience totaling six (6) full-time years may be considered. ● Two years of full-time experience in IT support (such as supporting computer and device hardware and software
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artificial intelligence with a preferred focus on computer vision and medical image analysis. Preferred Qualifications: PhD in Medical Physics, Bioengineering, Biomedical Engineering, Physics, Computer
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, Electrical and Computer Engineering, or a closely related field. ● Proficiency in MATLAB or Python. ● Prior experience with Neuroimaging analysis (using FSL, AFNI, SPM, etc.) ● At least one
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Job Description Required Qualifications: (as evidenced by an attached resume) * Recent Ph.D. degree (or foreign equivalent) in Biomedical Engineering, Medical Physics, Electrical and Computer
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evidenced by an attached resume): PhD or MD/PhD in a quantitative life sciences or tech-bio discipline, such as computational chemistry, chemistry, computational biology, biophysics, biomedical engineering
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, Electrical and Computer Engineering, or a closely related field. ● Proficiency in MATLAB or Python. ● Prior experience with Neuroimaging analysis (using FSL, AFNI, SPM, etc.) ● At least one
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programs, partnerships, and student-centered strategies. This role combines direct program oversight with supervisory responsibility, cross-divisional collaboration, and continuous assessment to ensure high
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into effective programs, partnerships, and student-centered strategies. This role combines direct program oversight with supervisory responsibility, cross-divisional collaboration, and continuous assessment
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Postdoctoral Associate Required Qualification: (as evidenced by an attached resume) Ph.D.(or foreign equivalent) in Mechanical Engineering, Electrical Engineering, Computer Science, Robotics, or a
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into effective programs, partnerships, and student-centered strategies. This role combines direct program oversight with supervisory responsibility, cross-divisional collaboration, and continuous assessment