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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic
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conduct world-leading research in the development of microwave-based technologies for medical diagnostics, treatment, and monitoring. Our research activities span computational modeling, algorithm
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will take advanced courses to build and deepen your skills, implement and evaluate algorithms, and develop your ability to write and present scientific work. We are a supportive team that will welcome
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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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Networks, and ICT Services & Applications. Your role Design intelligent agent architectures leveraging large language models (LLMs), planning algorithms, and secure transaction protocols tailored
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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Europe | 23 days ago
manufacturing, development of machine learning algorithms and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen