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a relevant field (e.g., transportation, human-computer interaction, architecture, cognitive science, or related disciplines). Experience with XR technologies, including development in Unity or Unreal
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(DynamX) to capture arterial behaviour. Apply computer modelling to process, interpret, and integrate experimental results. Collaborate closely with biomedical engineers, clinicians, and basic scientists
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of the IMV group and of this PhD project. · A brief description of any prior experience in visualization, human-computer interaction, immersive and interactive computer graphics, or related areas. · A CV that
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psychology, organizational behavior, computational social science, or sociology. PhD after one year of employment. Technical Skills or Knowledge: Conducting field, computer, web-based, and interpersonal
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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AI, human-AI collaboration systems, computer vision (CV) models, and natural language processing (NLP) models. Candidates with expertise in any of these areas are encouraged to apply, as the position
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tools Computer science » Systems design Engineering » Chemical engineering Engineering » Computer engineering Engineering » Design engineering Engineering » Industrial engineering Engineering » Materials
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Max Planck Institute for the Study of Crime, Security and Law, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | about 4 hours ago
, psychologists, sociologists, mathematicians, and computer scientists work together to understand the causes and consequences of criminal behavior and to develop effective interventions for the prevention of crime
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to establish an international quantum computing programme, funded by the Novo Nordisk Foundation, that will drive research and innovations at multiple levels - from developing scalable quantum processor
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longer sustainable. This project pioneers a new paradigm: we design smart, low-power digital AI co-processors that learn and correct the imperfections of their analog counterparts in real-time. As a PhD