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Europe | about 1 month 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
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international teams, and value creative approaches to research. You communicate fluently in English, both in writing and orally. We Offer: Access to an international network of scientists, policymakers, and
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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the English Our offer A vibrant research community in an open, diverse and international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with
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with TMS at specific oscillatory states and measure the subsequent network response with fMRI in the context of different cognitive paradigms. What you’ll be doing Conducting data collection and analysis
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differences in ecologically and economically relevant life history traits are regulated at the molecular level. Variation in a key Atlantic salmon life history trait, maturity age, is strongly influenced by
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and networks, we are truly an international place of knowledge. We are seeking to recruit a PhD candidate for a comprehensive interdisciplinary project to contribute to developing a community-based
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(LLMs) and state of the art methods in NLP. Has a demonstrable interest in misinformation countering or climate communication. Is willing to acquire knowledge of Social Network Analysis methods and
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value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions
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Description Ageing infrastructures, urbanization, and climate change are intensifying the vulnerability of critical infrastructures (CI), high-tech industries (HTI), and communities to cascading hazards