138 computational-model-"INSAIT---The-Institute-for-Computer-Science" positions in France
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, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns
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About us The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Luxembourg Centre for Socio-Environmental Systems strives to grow into an internationally recognised research hub for a sustainable and equitable...
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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available to work on computational models of artificial evolution for aptamer design, expected to start between November 2025 and February 2026. Aptamers are often obtained through rounds of in vitro
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well as computational modeling. The development and numerical implementation of novel methods has become a key issue in modern oncology, both in terms of understanding the biology of cancers and for medical oncology
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Job description We are recruiting postdocs to contribute to research projects in the Mathematical Modelling of Infectious Diseases Unit, at Institut Pasteur in Paris. The candidates will be expected
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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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biology with computer science, mathematics, chemistry, and physics. Research carried out within DYNABIO teams spans a wide range of biological models and addresses fundamental questions in biological
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on Artificial Intelligence Organization, 2017. - C. Bouveyron, P. Latouche and R. Zreik, The Stochastic Topic Block Model for the Clustering of Networks with Textual Edges, Statistics and Computing, vol. 28(1