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Statistics is offering a postdoctoral scholarship within the project “Phase transition in aggregation processes and network models”. The scholarship is full time for two years with starting date 1 January
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University of Technology , where you will develop explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment
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aims to digitalize the sense of smell, laying the foundation for understanding how olfaction works in humans and for building AI models that simulate olfactory experiences. The research will focus
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medicine, with a particular focus on spinal cord and peripheral nerve injuries. The projects involve work on various aspects of nerve regeneration and tissue engineering using both in vitro and in vivo model
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explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment, collaborating with leading experts in AI, mathematics
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. The work involves areas such as AI-assisted automation engineering, digital twins, semantic modeling, secure data exchange, and reconfigurable production architectures. The research is carried out in
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focus on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid
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modeling, secure data exchange, and reconfigurable production architectures. The research is carried out in collaboration with leading industrial and academic partners within large-scale Horizon Europe
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treatment. Develop methods and models that can predict the course of the disease by analyzing detailed data on the immune system and metabolism. We are conducting a large study, the CoVUm study, involving 579
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on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid state