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university degree (diploma, master's degree) in transport or traffic flow or related study programs. Solid knowledge of at least one programming language, preferably Python, experience in model-based
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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
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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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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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children with autism and eating behavior challenges. This research explores how large language models (LLMs), interactive robotics, and multimodal technologies can support creative expression and
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relevance. Your Tasks Antibody–Drug Conjugates (ADCs) are a rapidly advancing class of cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic agents. Upon
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combine engineering design principles with stake-holder engagement tools to support decision-making under uncertainty. Using methods like agent-based modelling, quantitative resilience and risk analysis
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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also collaborate with the “Cognition Perception Usages” team at LISN, led by Jean-Claude MARTIN, who specialises in psychological theories and models of motivation, personality, and social interactions
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operational performance. Based on feedwater composition (salinity, monovalent/divalent ion ratios, and valuable elements), you will model and design ED configurations that produce tailored concentrate streams