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Dynamics (AIMD), and Machine Learning (ML) tools to develop theoretical electrocatalytic frameworks. Hereby, the project will challenge existing research on catalysis, move the boundary of fundamental
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, develop methods to speed up this development by focusing on machine learning techniques to address sustainability challenges in chemistry research. We will explore novel pathways to process design and
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Models and Machine Learning techniques able to "let the data speak" and assess interactions between multiple determinants. The present PhD will focus on the sustainability side of the project and the
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of the doctoral student The PhD project will aim at integrating single cell clonal, spatial and dissociated cell transcriptomics data for 3D neurodevelopmental reconstruction using a machine learning approach and