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Field
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investigate how machine-learning based algorithms can be used to personalize the user experience. The goal of this personalized user experience is to enable each individual user to discover their own
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. Construct machine-learning models for feature-based molecular property prediction and drive the inverse design of ligands with engineered properties. Develop machine-learned interatomic potentials trained
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, we link micro- to macro insights by using a wide range of methodologies from (behavioral) experiments, to surveys, spatial econometrics, simulations and agent-based models. The research is embedded
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. The models will be based on eco-evolutionary theory and informed with ecological and evolutionary data from public databases and published papers. This combined theoretical and data driven approach includes
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photo-bases. The work will focus on modeling of adiabatic and nonadiabatic photochemical processes to capture excited states dynamics using an array of ab initio molecular dynamics methods for excited
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agreement (preferably, 2025 Q2) Duration: 1 year, renewable based on performance and funding availability About the Position We are seeking a highly motivated Postdoctoral Researcher to lead research
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Applications Starting date: Upon agreement (preferably, 2025 Q2) Duration: 1(+1) years, renewable based on performance and funding availability About the Position We are seeking a Postdoctoral Researcher to
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/w) fixed-term postdoctoral position in Simulation and Modelling. The position focuses on designing and implementing the agent-based modeling component of research projects in code, requiring
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and conducting experiments using various mouse models of disease. This position involves investigating how bacterial agents modulate immune responses to develop novel therapeutic strategies, with a
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based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa. UM6P is an institution oriented towards applied research and