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, including intracranial EEG (iEEG/SEEG), local field potentials (LFPs) and single-unit recordings. The position has a strong focus on scientific software development in Python, data engineering and signal
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). Complex visual anomalies are: (1) logical defects where models must detect and verify the relative positioning logic between different objects or entities within the scene. Examples include checking
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selectivity between materials and minimize plasma-induced damage, will be evaluated as part of this study. To achieve this objective, it will be necessary to understand the etching mechanisms of the different
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aerosols. - Visualization and post-processing tools: Proficiency in visualization tools (e.g., Python) and data post-processing tools to analyze simulation results and generate graphs, maps, and diagnostics
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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning
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microbiology, bacterial genetics, CRISPRi approaches, and bioinformatics analyses to identify the molecular and genetic determinants underlying strain-to-strain differences in stress responses. In particular
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) to soft matter or related systems; basic knowledge of scattering data modelling is essential. Data analysis skills and programming experience in Python or MATLAB. Ability to work effectively with multi
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should have a good knowledge of scientific programming (e.g., Python, C, Fortran) and finite-element or finite-difference schemes. It will be an asset if the candidate has prior research experience in
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of AI approaches at different levels of the model chain, i.e. by implementing end-to-end learning frameworks that link data, forecasts, and operational decisions, while incorporating diverse contextual
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, particularly in light of the rise in chronic diseases, the necessary strengthening of prevention efforts, or the possible resurgence of epidemics; socio-economic inequalities and differing capacities to access