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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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use the data to train deep learning models of cancer. This allows us to identify systems-level mechanisms that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. We
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of green chemistry in a life cycle perspective, upscaling process data from low TRL, and integrating quantitative LCA modelling with socio-technical systems approaches to make well-founded assumptions about
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devices (including electron-beam lithography), and characterization and measurements of final metasurface devices. The experimental work is often complemented by optical simulations, primarily using
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project focusing on developing controlled crystallization of metal salts. The work includes the design and experimental study of simple model systems as well as more applied studies. The applicant should
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of AI and edge computing, particularly in network optimization, distributed decision-making, and large-scale foundation models. We seek candidates interested in theoretical analysis and optimization
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be a role model for doctoral students. Well-developed analytical and problem-solving skills are a requirement. The research is expected to use methodology from networking, communication theory, machine