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SD-26084 – POSTDOCTORAL RESEARCHER IN THE CHEMICAL VAPOR DEPOSITION OF COVALENT ORGANIC FRAMEWORK...
with members of the hosting group to build up a deep understanding on the electrochemical behaviour of the produced thin films and develop strategies to enhance their functional properties
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SD-26085 POSTDOCTORAL RESEARCHER IN THE OXIDATIVE CHEMICAL VAPOR DEPOSITION OF FUNCTIONAL BUILDIN...
to build up a deep understanding on the electrochemical behaviour of the produced thin films and develop strategies to enhance their functional properties. The postdoctoral researcher, integrated to a very
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attribution, representation analysis, causal probing, and mechanistic circuit analysis. The postholder will also develop predictive models using modern deep learning frameworks (e.g., PyTorch) and evaluate them
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
. Preferred Qualifications, Competencies, and Experience Programming skills (e.g., python, bash scripting, Fortran, C++ and CUDA), expertise in computational modeling (such as Deep Learning, Molecular Dynamics
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the following areas: deep learning, reinforcement learning, imitation learning, robot perception, navigation, and manipulation. Experience with whole-body control, humanoid or multi-DOF platforms, and
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Essential skills, knowledge and experience: Experience with machine/deep learning development Data-Centric AI Knowledge Notions of cybersecurity and networks are optional Spoken and written English Desirable
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on animal behaviour and welfare in pigs, where behavioural science is integrated with artificial intelligence and deep learning for the assessment of animal welfare. You will have a central scientific role in
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data (PET, CT, Magnetic Resonance Imaging with Late Gadolinium Enhancement – MRI-LGE) and clinical variables. The approach encompasses unsupervised multimodal registration, three-dimensional deep