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their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
position will include, but is not limited to, multimodal+embodied semantics, human-like language generation and Q&A/dialogue, and interpretable and generalizable deep learning. The duties of the postdoctoral
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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. Broward College places special importance on helping under - prepared students achieve academic success. Candidates should demonstrate (1) a mastery of their specific discipline; (2) a deep commitment to
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explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The successful candidate will need to be eligible for UK security clearance in principle
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. The Department of Computer Science is home to a dynamic and interdisciplinary group of 30+ full-time faculty members and over 2000+ students across its BS, MS, and PhD programs. The department is committed
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twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL