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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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researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
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computer scientist with experience in bioinformatics, solid programming skills and knowledge in 3D protein structures. Machine learning skills and knowledge of Web development are a plus. Good interpersonal
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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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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling
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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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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