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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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correspondence between algorithmic computation of differentials or solutions to differential equations and the logical principles at work in linear logic and associated lambda calculi. The postdoctoral researcher
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. Job Description: Two postdoctoral researcher positions are available in the laboratory of Dr. Sarah Kim (https://pharmacy.ufl.edu/profile/kim-sarah/) to apply modeling and simulation approaches
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resonance imaging data among other imaging modalities, machine learning methods for prediction, treatment effect estimation, and contribute to understanding brain biomarkers of Alzheimer’s disease and their
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mathematics curriculum on success and retention in STEM disciplines, though applications from all fields of DBER are welcome. The DBER postdoctoral fellows will hold a 12-month appointment and teach one three
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, or similar, and a degree in Environmental Engineering, Environmental Science, or a related quantitative field. Position 2 will focus on large-scale data analytics and machine learning. Applicants should have
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enterprises (SMEs). The postdoc will work at the intersection of cybersecurity, machine learning, and human centered system design, contributing to the research on privacy aware monitoring, attacker modelling
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Union within the project “A Comprehensive Trustworthy Framework for Connected Machine Learning and Secure Interconnected AI Solutions (CoEvolution)”, - CUP F23C24000210006 – selection code: ipd_10D_0426_09/IINF
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AI and physics‑based simulation for complex mechanical systems. We are now seeking a postdoctoral researcher for a project aiming at physics‑informed autonomous control of machines operating in rough
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
. The postdoctoral fellow will play a central role in advancing new statistical and machine learning methodology. Areas of focus include (but are not limited to): * Clustering and unsupervised learning * Dimension