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, funded by the ANR P2S2 project. The position is available initially for a fixed-term duration of 2 years, with the possibility of extension for 1 further year. The P2S2 project aims at developing parton
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transmitters, DPD algorithms, and analog/mixed-signal challenges. For more details about the DISRUPT project, please visit: https://elca.tudelft.nl/Research/project.php?id=243 https://www.linkedin.com/posts/tu
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systems Develop technical work methods in production of projects and analyses of research data Design methods for data mining, algorithms, and application of complex statistical reasoning and statistical
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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary
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silico approaches. This may include mathematical modeling of biological systems, machine learning and artificial intelligence methods, and the development of innovative algorithms and software pipelines
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Neurobiological discoveries have been fueled in recent years by rapid development of optical imaging tools. Over the last decade the Laboratory of Neurotechnology and Biophysics has developed a wide portfolio of
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focused on using advanced numerical methods to explore low energy dynamics in strongly interacting quantum spin systems. The candidate will develop and implement advanced algorithms to investigate
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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methods that reduce compute, energy usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and
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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by