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an independent impact assessment of potential climate interventions in the Arctic marine environment through laboratory experiments and computer modelling. The team will develop physical, climate and ecosystem
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, particularly GBS, continuous-variable QC Experience with numerical simulation, statistical estimation, or probabilistic modeling. Programming proficiency (Python, Matlab or C++), especially for numerical
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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-world medical applications? Do you want to design next-generation protein therapeutics using cutting-edge generative models and validate them in the lab? Join a collaborative PhD project at DTU
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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. These goals require research of international calibre and the development and application of advanced technologies to support the needs of our numerous industry partners. The RO works in a team environment with
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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, foreseen in the application: 1-Development of the SUPERB framework 2- Definition of building classes and numerical models for physical vulnerability assessment 4-Definition of baseline data reflecting
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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with GKN Aerospace Sweden with partial work there and combines numerical and experimental research. Project overview The purpose of this project is to contribute to the development of an ultra-efficient