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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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. In 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
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. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in methods for causal inference in observational data, is strongly preferred. Using various
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datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning). The goals are to develop new computational methods that allow the scientific inference
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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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Organizing meetings and workshops to promote awareness and advocacy Your profile Master's degree (or soon-to-obtain) in Psychology, Cognitive Science, or Education A track record of interest in technology
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. We will link molecular programs in specialised myonuclei to sensory-motor coordination sensory-motor coordination through eye-tracking and visual acuity assessments (collaboration with NeuroPSi Paris