29 postdoctoral-machine-learning "https:" Postdoctoral positions at Stanford University
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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connections between the lab, classroom, and society. Required Qualifications: Highly motivated postdoctoral researcher with extensive experience with item response theory models, computer adaptive testing, and
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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution
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. The fellow will also work closely with SCEC Senior Machine Learning Engineer Dr. Lauren Klein Dubin, who will provide day-to-day supervision of the fellow's technical work. The fellow will have opportunities
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ability to quickly learn and master various computer programs. Strong record of peer-reviewed publications. A PhD, MD or equivalent with prior relevant training in Immunology, Biology, Bioinformatics
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, and those with experience analyzing biobank data and/or expertise in machine learning will be prioritized. Candidates who demonstrate readiness to define and lead new research projects are highly
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). Experience applying machine learning or AI methods in these fields is an advantage. The ideal candidate should also be comfortable structuring, linking, and analyzing large datasets that include dense
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Postdoctoral Affairs. Appointment Start Date: Flexible, but no later than Fall 2027. Group or Departmental Website: https://ai4pb.stanford.edu/(link is external) https://www.pascl.stanford.edu/(link is external
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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data