81 algorithm-development-"Prof"-"Prof" Postdoctoral research jobs at University of Washington
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Position Summary The postdoctoral fellow will develop artificial intelligence applications to support characterization of medical data with a focus on radiology image, radiology reports, and
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interactions, nuclear structure and reactions, electroweak structure, and lepton-nucleus scattering. The candidate will contribute to advancing statistical and computational algorithms to extend the capabilities
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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Position Overview School / Campus / College: College of Arts and Sciences Organization: Speech & Hearing Sciences Title: Postdoctoral Scholar - Behavioral and Neural Development of Social
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. Qualifications Required Qualifications: Completed PhD in biomedical engineering, electrical engineering, physics, or a medical imaging related field. Experience with developing advanced pulse sequences
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. Proficient with running machine learning algorithms (e.g., Random Forest, CART) and regression models (e.g., SAR, LME) to derive ecological insights from big data sets. Experience developing reproducible and
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development. • Genotype-Phenotype Correlations in 9p-Related Syndromes: Investigating the genotype-phenotype correlations in 9p-related syndromes (e.g., 9p deletion syndrome, 9p duplication syndrome
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to achieve the following objectives: 1. Characterize 3-D Urban Structure and Change: Utilize data from multiple remote-sensing platforms and deep learning algorithms to generate high-resolution maps of 3-D
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, establish advanced manufacturing routes for these polymers and implement computational algorithms to assist their optimization. The RISE Polymer Lab is dedicated to developing the next generation of robust
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the formation of the isthmus of Panama and its impact on the evolution of plants in rivers). This collaborative project will integrate genomic, paleontological, and geological data to unveil how riverweeds