62 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Duke University
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Duke University, Electrical and Computer Engineering Position ID: Duke -Electrical and Computer Engineering -POSTDOCYIRANCHEN [#30336] Position Title: Position Type: Postdoctoral Position Location
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, Duke University Biology Department to study how archaeal microbial communities respond to stress in hypersaline environments. A PhD in computational and/or experimental biology is required in fields
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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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with various methods that can incorporate domain-based constraints and other types of domain knowledge into machine learning and applying these techniques to problems in computational creativity
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, United States of America [map ] Subject Areas: Chemistry / Bioinformatics , Chemical biology , Computational Appl Deadline: 2025/09/15 11:59PM ** Position Description: Apply Position Description Job Opening: Postdoctoral
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data, identifying structural errors in the dataset, and for maintaining a record of all steps from data extraction to dataset assembly · Fitting of machine learning models · Development of instrumental
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, and Alzheimer's research. Qualifications: · Ph.D. in Computer Science, Biostatistics, Bioinformatics, Biomedical Engineering, or a related field · Expertise in deep learning and its
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team to unravel the mysteries of membrane ion and lipid transport and their roles in various diseases. Minimum Requirements: PhD in biochemistry, biophysics or cell biology Preferred Qualifications
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policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
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computational and data analytical methodology development and implementation; experience in supervised and unsupervised machine learning, low-dimensional models or deep learning models, and willingness to learn