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protein–protein interactions that play crucial roles in biological processes such as cell signaling and cancer. The successful candidate will contribute to our efforts to map these interactions
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) signal processing, machine/deep-learning and computational linguistics. The team mobilizes them to produce methodologically sound research in response to some of the challenges posed by the nature and
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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and erosion for 60 years. One of the main objectives is to acquire fundamental knowledge about the processes controlling environmental risks related to the dynamics of metal contaminants (speciation
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on the ERC-funded project ‘Understanding the Consequences of Major Health Crises for Education: Learning from the COVID-19 Pandemic (LEARN)’. The LEARN project: Health crises, natural disasters, and violent
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lie at the crossroads of multiple disciplines and involve expertise in optics, electronics, image and data processing (including machine learning), photophysics, chemistry and biology. The position is
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, benefiting from welcome and inclusion schemes, training and internal mobility. It means participating in an academic, scientific and human adventure. It means committing to meeting the challenges of the 21st
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the project team, you will ensure the simulation of drone missions using state-of-the-art tools for AI learning and demonstration. You will be responsible for producing training data for vision models and
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challenges in stem cell research, aging and disease modeling. The group employs methodologies from different areas of mathematics, engineering, and physics, and integrates multiple sources of biological
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed