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Field
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, and adapt to human interaction. This requires rethinking both what we measure and how we design models. The PhD candidate will: Create datasets and benchmarks that capture emotional cues, conversational
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: This PhD project aims to uncover how plants perceive glycan-based Damage-Associated Molecular Patterns (DAMPs) through novel receptor kinases characterized by our group (Martin-Dacal et al., 2022; Molina et
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contributing to new research methods in human-AI collaboration? Then we are looking for you! We are hiring a technically strong, creative, and socially motivated PhD candidate to join the international
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immune cells in cell culture and murine models of inflammation and cancer Collecting, analyzing and annotating MRI data Combining MRI and mass spectrometric imaging data in data base for quantitative MRI
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Job Description DTU Compute and the Pioneer Centre for Artificial Intelligence are excited to offer a PhD position for a talented and motivated student to join our lab at DTU led by Theodora
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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, instrumentation, acceleration techniques, and biological techniques. The laboratory has also developed important on-site research infrastructure and technological platforms. IJCLAB bases its recruitment policy
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-based modelling, quantitative resilience assessment, and risk analysis to simulate and optimise resilience strategies. The framework will be tested and refined through pilot studies in collaboration with
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and optimize specific functions. The ICMCB carries out fundamental research on model materials and/or materials with potential applications. The ICMCB is a UMR with an average of 280 agents (permanent
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will be to: identify policy mechanisms that can change infrastructure affordance and lower infrastructure use develop an agent-based model that regards infrastructure as a socio-technical system reveal