42 phd-position-in-image-processing Postdoctoral positions at Carnegie Mellon University
Sort by
Refine Your Search
-
significant impact on the world around us. ECE is seeking a Postdoctoral Research Associate to join the team! This position will require an in depth knowledge of a specialized field, process, or discipline and
-
computer vision, machine learning, or bioinformatics applied to biological questions. Position Details: As a postdoctoral scholar in the Bridges Lab, you will: Develop and lead research projects aligned with
-
. Qualifications: Doctorate degree required Background in optical imaging, data and signal processing Expertise in machine learning Experience in human subject measurements Background in optical tomography as
-
of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
-
of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
-
Details Posted: 16-Feb-25 Location: Pittsburgh, PA Categories: Academic/Faculty Internal Number: 84172 Postdoc Positions in Image Analysis The Xu lab at the School of Computer Science at Carnegie
-
. The project will initially be associated with a NPS project that seeks to leverage Operation IceBridge elevation change data to refine projections of glacier changes in Alaska through 2100. Additional
-
and computer engineering. Working closely with interdisciplinary researchers. Performs other duties as assigned. Inclusion and cultural sensitivity are valued proficiencies at CMU. Therefore, we are in
-
and computer engineering. Working closely with interdisciplinary researchers. Performs other duties as assigned. Flexibility and cultural sensitivity are valued proficiencies at CMU. Therefore, we
-
are highly desirable. For the quantitative position, the applicant must have a PhD in computer science, statistics, or related field. Experience with empirical studies of software artifacts and social network