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includes, but is not limited to: photonic data processing and communication systems; AI-driven optical signal processing and network optimisation; machine learning for photonic systems modelling, control
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information, quantum technologies and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your
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, Higgs physics, particle dynamics in the early Universe, collider phenomenology, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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processing, machine learning, statistics or related fields. Demonstrated expertise in ML/AI, with prior experience of applications in the healthcare domain, particularly in cancer research considered a strong
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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through applied research programmes. Faculty in the ICT Cluster undertake funded industry-relevant research, teach courses in Computer Science, Computer Engineering, Information Security and Software
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theoretical approaches to machine learning and artificial intelligence. Specific Requirements Having the status of a doctoral student; Strong mathematical skills and knowledge; Experience in math/coding
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cybersecurity expertise with modern AI techniques such as machine learning, deep learning, or large language models? Then we strongly encourage you to apply. You will join an established team with 25+ members