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and associated environmental impacts. Contribute to short-term (2026 to 2030) and long-term (2030 to 2050) verticalisation forecasting models based on machine learning, and to their validation against
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(or similar): Coherent diffractive imaging, especially ptychography. Sparse sensing, optimization, or Bayesian experimental design. Machine learning for imaging. Synchrotron experiment experience. Semiconductor
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. Sparse sensing, optimization, or Bayesian experimental design. Machine learning for imaging. Synchrotron experiment experience. Semiconductor devices or metrology. We offer We offer a fully funded
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(or similar): Coherent diffractive imaging, especially ptychography. Sparse sensing, optimization, or Bayesian experimental design. Machine learning for imaging. Synchrotron experiment experience. Semiconductor
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Understanding human motivation requires methods that go beyond questionnaires and simplified computer-based tasks. This project aims to develop more naturalistic, yet highly controlled, behavioral assays in which
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a new research collaborator with a PhD in building technology, preferably in the field of building materials and/or building envelope performance and/or building renovation. The candidate must be
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-reviewed journals; Support in funding acquisition; Contribute to laboratory activities, including PhD and Master student supervision and teaching assistance. Profile PhD in architecture, civil engineering
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lab members, the group's organoid/tissue-engineered infection models (airway, gut) to prioritize physiologically relevant hits Co-supervise PhD students and contribute to method development, data
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Profile PhD in microengineering, electrical engineering, mechanical engineering, applied physics, materials science, or a closely related field Strong hands-on experience in MEMS or micro/nanofabrication
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execution Analyze and interpret experimental results Write scientific articles for publication in peer-reviewed journals Present at international conferences Profile A PhD degree in the fields of chemistry or