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-to-confidence set conversion' framework recently proposed by the PI (Principal Investigator). The models of interest include deep neural networks with multiple layers and non-linear activations, extending recent
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, Saarbruecken, Saarland, Germany with Prof. Nadja Tarakina and 3 months at Spark Nano, Eindhoven, Netherlands with Dr. Paul Poodt. The salary will comply with the rules of the 2025 MSCA Doctoral Network program
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the rules of the 2025 MSCA Doctoral Network program under Horizon Europe and consists of: a living allowance (country correction coefficient applies), a mobility allowance (€710/month), and, if applicable, a
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an organization arising from inappropriate user actions. It seeks to anticipate malicious actions and optimize the collection of evidence necessary for conducting forensic investigations to determine liability in
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digital strategies. This includes robotic automation of repetitive tasks and the use of artificial intelligence to optimize experiments and exploit composition-processing-property relationships
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Mission: Support research to improve the management of renewable energies. Functions to be developed: Develop machine learning algorithms. Implement and validate computational models. Plan networks with
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to optimize the instrumental resources available. In addition, the NMR staff, also takes care of the instruments maintenance, update and new experiments implementation. Responsibilities (performed under
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screening, and automated experimentation to accelerate materials discovery and optimization. The researcher will work across the groups of Prof. José Berrocal and Prof. Carla Casadevall at ICIQ and interact
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malignancies, with the final aim of finding a cure for these diseases. It was created in 2010, and since then has experienced an exponential growth. The IJC is also part of the network of Excellence Research
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. The researcher will contribute to the development of novel flexible neural interfaces and their physical and chemical characterization. By using nanofabrication, this project seeks to optimize stimulation