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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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& Machine Learning • Clinical pathways and decision support for patients with acute chest pain • AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis • Speaking
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, Lattice QCD , LHC , Neutrino , Neutrino physics and Astrophysics , Particle Theory , Phenomenology , astrophysics , Machine Learning Physics / Astroparticle Physics , Cosmology , Dark Matter and Axion
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 26 days ago
for individuals that are interested in pursuing a PhD in economics or finance. The chosen candidate will also gain valuable experience in the application of machine learning and Bayesian inference methods
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The Department of Electrical & Computer Engineering (ECE) at The University of Alabama is recruiting motivated PhD students to join our cutting-edge research program.Qualified applicants can
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for this position focused on machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in collaboration with Brookhaven Lab staff, the Department of Energy (DOE), and
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the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago
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. Depending on the Research Educator's expertise, the stream may investigate topics such as: Using AI and machine learning to understand or address social challenges (e.g., health disparities, misinformation