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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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causal inference methods (e.g., directed acyclic graphs) would be an asset Fluent in reading, writing, and speaking scientific English Required Skills : Experience in data management and analysis of cohort
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integrated Optics / Photonics or a related discipline. ● A strong track record demonstrating excellence and creativity. ● Experience in design and simulation of integrated photonics components, including
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tomography (SPECT) is an imaging technique that tracks the 3D distribution of a radioactive tracer administered to a patient to monitor certain biological functions. The long acquisition times (10-40 minutes
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skills, and proven track-record in at least two of these three areas: fluid mechanics, active matter, and reinforcement learning. Website for additional job details https://emploi.cnrs.fr/Offres/CDD
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particular focus on digital methods and tools. The C²DH's ambition is to venture off the beaten track and find new ways of doing, teaching and presenting contemporary history of Luxembourg and the history
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obtained from ex vivo robotic tests will inform multiscale numerical models of tissue mechanotransduction, calibrated using in vivo murine gait analysis and behavioral tracking provided by IRMB
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, or colloidal nanocrystal manipulation. A track record of scientific publication is essential for application. A minimum of 15 publications is required to apply (strict rule). The candidate should have a strong
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particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required skills : We