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prestigious ERC Consolidator Grant in a great interdisciplinary institute in Amsterdam. Join us! Are you passionate about machine learning, natural language processing and generative AI? We are seeking a
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), this postdoctoral project will focus more explicitly on socio-emotional processes in team learning, investigating how emotions, motivation, group climate, and interpersonal regulation shape learning and performance
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, global ocean circulation and height systems. In addition, the temporal variations of gravity and the geoid help to measure mass exchange processes in the Earth system. Knowledge about the time-varying
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manufacturing capabilities, allowing us to manufacture more versatile optical systems, including lasers, cavities, frequency references and more. If successful, you will be able to join OpticsFoundry and bring
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and imaging capabilities, and on applying THz (emission) microscopy to study 2D materials and 2D heterostructures. The microscope will use femtosecond lasers to generate and detect terahertz pulses
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to achieve continuous Bose-Einstein condensation [Nature 606, 683 (2022) ]. We are building two types of such clocks: a superradiant clock and a zero-deadtime clock. A superradiant clock is a laser that lases
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process We invite you to submit a complete application using the apply-button. The application should include a: Cover letter in which you describe your motivation and qualifications for the position
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processing, and user-friendly GUI-based analyses for clinical and physiological research. You will combine Python-based software development, biomedical signal processing, and FAIR data design, and contribute
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Models to push the frontier where computer vision, physics simulation, and embodied AI converge. Join Us! This position is part of a collaborative research programme between the University of Amsterdam
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approaches treat NP design as static property prediction. This project takes a fundamentally different approach: using generative models to propose novel NP formulations and coupling them with explainability