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Field
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, or chaotic neural networks. Experience with network dynamics. Experience with time-series analysis. Experience with stochastic processes. Experience with computational modeling of biological systems
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on the mathematical theory of deep learning as part of the joint NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
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engages in continuous professional development. Desirable criteria Experience of network analysis/graph theoretical techniques; Experience working with data related to mental health. Downloading a copy of
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achieved in fabrications of coupled double-drum resonator networks, financially supported by EU project Chist-ERA NOEMIA and French ANR-MORETOME projects. A simple reservoir computing function and training
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
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an interdisciplinary team. Your tasks Conduct physical vapor deposition experiments using advanced PVD processes such as synchronized HiPIMS Perform in-depth materials characterization and surface analysis Apply and
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21 Sep 2026 Job Information Organisation/Company Łukasiewicz Research Network – PORT Polish Center for Technology Development Research Field Neurosciences Researcher Profile Recognised Researcher
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biology analysis, bioimaging with advanced image analysis, plant transformation, AnalyzER software for analysis of cellular structures) • Experience with statistical analysis • Excellent team
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pavement networks. This position will focus on modeling and optimizing pavement performance under evolving climate and hazard conditions. This position will advance modeling of pavement life-cycle
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funded NIH R01 project dissecting the SOX4/SOX9 transcriptional regulatory network that governs biliary development in Alagille syndrome and advancing the therapeutic potential of targeting this network in