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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
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, band selection Heterogeneous network architectures, including terrestrial and non-terrestrial networks Deep learning for wireless communication problems, particularly in areas such as spectrum management
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
Area of research: Laborkräfte Job description: Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic nodule fields (m/f/d) Background While some companies
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 22 days ago
increasingly utilizes big data, satellite imagery, register data, and advanced methods such as deep learning and neural networks to address major societal challenges related to spatial inequalities and
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Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of machine learning and deep neural networks Free Probability aspects of Quantum
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engineering, neuroscience, computational biology, or a closely related field ï‚· Strong oral and written communication skills ï‚· Demonstrated motivation, initiative, and attention to detail ï‚· Deep interest
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An exciting postdoctoral position is available in the exciting field of mathematics of deep learning, under the joint supervision of Prof. Alex Cloninger and Prof. Gal Mishne at UC San Diego. This NSF-funded
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries