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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat
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the programme period starts on commencement of the position. The position is part the Marie Sklodowska-Curie Actions Doctoral Network “ENDAMR: Exploring Novel Drivers of Anti-Microbial Resistance
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of your transferable skills via a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and
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economics at the ifo Institute under the supervision of Prof. Dr. Ludger Wößmann, LMU, and Dr. Henning Hermes. Participation in the structured doctoral program at the Munich Graduate School of Economics (MGSE
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To meet global Net Zero targets, we must urgently transform the chemical industry to adopt green, sustainable methods to reduce their environmental impact. This three-year PhD project will develop
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging
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-time Mode of study Hybrid Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application deadline No specific deadlines Tuition fees per semester in EUR None Combined
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for blockchain-based systems. Develop mathematical and computational models for simulating and analysing various economic properties of blockchain-based systems. Design and evaluate token economies and governance