18 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Virginia
Sort by
Refine Your Search
-
Qualifications PhD degree in computer science, data science, or related fields. Effective written and verbal communication skills Robust machine learning and natural language processing skills Proficient computer
-
The Carter G. Woodson Institute for African American and African Studies invites applications for residential Post-Doctoral Research Associates, beginning in July 2026 (must have PhD in hand by June
-
include autism spectrum disorder (ASD), ADHD, developmental delay, language disorder, intellectual disability, anxiety/mood disorders, and learning disabilities. Participation on a stepped-care
-
Science, Physics, Engineering, or a related field, earned within the past six years Experience with AI and machine learning Excellent written and spoken communication skills Demonstrated ability to produce high
-
Lawmaking, and will have the opportunity to teach one class in the Batten School. A particular research focus on lawmaking in American state legislatures and/or the U.S. Congress is welcome. The Center
-
the supervision of the Principal Investigator. Qualified candidates must have a doctoral degree, preferably a PhD in psychology, neuroscience, or biological sciences by the appointment start date. Extensive (3
-
, Economics, or a related field, earned within the past six years Strong computational and statistical skills Experience with large-scale data analysis and machine learning Proficiency in scientific programming
-
extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs. Salary Range: The anticipated salary is $62,000 Exemption Status: This is an
-
molecular, biochemical, and behavioral manifestations. We have collaborations with other labs that enrich the overall research experience. QUALIFICATIONS Applicants must have PhD and/or MD (or equivalent
-
data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world