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synthetic fuel reactors. Tasks include gas handling, system diagnostics, thermal integration, and performance evaluation under variable power inputs. Data Analysis and Machine Learning: Collect and process
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), aiming to bridge neuroscience and electronics. The project integrates expertise from circuit design, machine learning, and neurotechnology to deliver innovative solutions for applications such as brain
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of computational chemistry. Applicants can have a background from cheminformatics including RDKit, machine learning applied to chemistry, and molecular modeling Our group and research- and what do we offer? Our
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needed to achieve these temperatures, the control cables connecting to the qubits are often more than 2 meters long. At the same time, a quantum computer powerful enough to solve problems beyond the reach
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Small case Studies of Successful Innovation Funding Methods The project will employ a combination of mainly quantitative methods, including machine learning (ML) and generative AI (GenAI) models
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and