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Field
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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models are deeply rooted in real-world biological data. The collaborative approach allows for the development of predictive models that bridge the gap between theory and experiment, with a focus on high
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will contribute to work on control theory
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operation of scientific instruments. Our team Strong Interacting Matter in the theory division of IJCLab focuses on nuclear theory and its applications to others fields of physics. Our team, is
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to identify and model the most efficient catalytic sites on NDs using advanced Density Functional Theory (DFT) calculations. The project seeks to revolutionize the design of ND-based catalysts by controlling
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department and the Plant Reproductive Strategies (SRP) team. Our team focuses on the evolution of plant reproductive systems, using diverse approaches including theory, experimentation, bioinformatics, and
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Location: Paris, Ile-de-France 75 005, France [map ] Subject Areas: Statistical Physics / Statistical Physics Theoretical Physics / Mathematical physics , Conformal Field Theory , Quantum Field Theory
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the field of modular forms theory and its connections with harmonic analysis. - Conduct research at the highest level - Collaborate with other researchers in the laboratory - Participate in the scientific
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Information Eligibility criteria Internationally recognized expertise in the field of asymptotic theory of random maps (including, in particular, a Ph.D. in mathematics or computer science in this field
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/theory, the key research questions, the data, key variables, and the methodological approach/research design to be used. 4. Writing sample (e.g., one of your publications or working papers) 5. Contact