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are planned for participation in several international conferences). Expected skills Knowledge and technical skills: • Master's degree (or engineering degree) in Evolutionary Biology, Ecological Modeling
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About us The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of...
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3 Mar 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique de Grenoble Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage
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French National Research Institute for Agriculture, Food and Environment (INRAE) | Toulouse, Midi Pyrenees | France | 24 days ago
Krause's Department at the Max Planck Institute for Evolutionary Anthropology (MPI-EVA; Leipzig, Germany), a world-leading institution in the field of paleogenetics. You will also collaborate with Denise
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due to increased competition over food resources and mating opportunities. This tension creates an evolutionary pressure to develop mechanisms that reduce costs and increase benefits [1]. Humans use
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attention may be given to the emergence of ecology as a scientific field, including its differentiation into branches such as biogeography, evolutionary ecology, or ecosystem thinking, and to the shifting
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algorithms for asthma. The methods to be employed will include cell culture, transcriptomics, proteomics, multiplex assays, flow cytometry, and machine learning. This project combines expertise in cell biology
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consistent thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in
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thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in terms of gradient
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validated algorithms. The objective is to identify sensorimotor signatures of fall risk that may improve current predictive models and contribute to the development of more targeted prevention strategies