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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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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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colleagues, in order to acquire new skills. • Design and synthesis of new molecules with photocrosslinking functionalities that can self-assemble on surfaces according to compatible patterns. This task will
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- pan-Arctic simulations with ISBA - learning how to use permaFOAM - gathering of data necessary to use permaFOAM on the Abisko site - analysis and comparison of the ISBA and permaFOAM simulations
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Prerequisites: PhD in applied mathematics or physics with a strong theoretical component Strong
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on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify
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/simulation programming - characterisation of various samples - supervising student (intership, PhD candidate) - writing articles - taking part in conferences This work will take place at ISMO within
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. To that aim, both Stein-based bilevel optimization, empirical Bayesian and unsupervised deep learning approaches will be considered. The recruited postdoc researcher will tackle both implementation challenges
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ExperienceNone Additional Information Eligibility criteria The postdoc should have a PhD degree in evolutionary biology, with expertise in bioinformatics, statistics, programming and/or modeling. Previous