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Field
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SD-26083 – POSTDOCTORAL RESEARCHER IN THE CHEMICAL VAPOR DEPOSITION OF METAL ORGANIC FRAMEWORKS F...
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-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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models and transformer-based architectures to construct high-dimensional design spaces. These models are integrated with Deep Reinforcement Learning (DRL) for fine-tuning or end-to-end learning, enabling
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month 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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day 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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methods (e.g., deep learning, generative models, representation learning) ● Experience working with large public biological datasets/repositories (e.g., GEO, SRA, UK Biobank, GTEx, etc
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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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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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approaches beyond standard deep learning methods. Demonstrated experience in academic research (e. g. through publications, conference contributions or comparable scientific achievements). Very good