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programming languages. Experience with DICOM data, medical-image registration, high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image
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) research experience in one or more of the areas of intelligent fault diagnosis and condition monitoring, machine learning and deep learning; and (c) demonstrated ability to undertake high quality academic
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University, Wallumattagal Campus, North Ryde The role We are seeking a Postdoctoral Fellow, to join our category theory group. This position is associated with Dr. Jean-Simon Pacaud Lemay's AFOSR grant FA9550
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University, Wallumattagal Campus, North Ryde The role We are seeking a Postdoctoral Fellow, to join our category theory group. This position is associated with Dr. Jean-Simon Pacaud Lemay's AFOSR grant FA9550
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English Postdoctoral Research Fellow position in remote sensing and modeling of the cryosphere Apply for this job See advertisement About the position We invite applications for a Postdoctoral Research
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The Volcanology, Igneous Petrology and Geochemistry group, under Prof. Froukje van der Zwan at KAUST is looking for an outstanding postdoctoral researcher for a 2-year position (extension possible
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architecture trait identification. The overall objectives of the project include: Deep understanding of plant water relations to extreme environmental stresses. Hands-on experience in measuring leaf gas exchange
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. Programming experience in Python, Matlab, and SQL. Mathematical modeling and data analysis. Machine/Deep learning (e.g. Pytorch, TensorFlow, JAX). City of Hope employees pay is based on the following criteria
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Stephen & Denise Adams Center for Parkinson's Disease at Yale School of Medicine | New Haven, Connecticut | United States | about 2 months ago
-generation AI models of gene regulation and disease progression. Our work is redefining Parkinson’s disease biology and enabling translational breakthroughs. The role Develop deep learning models across genome
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. You will develop and apply state-of-the-art deep learning methods for land cover classification and change detection using multi-source aerial and satellite imagery. Working within an interdisciplinary