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looking for a PhD Student (f/m/d) Development of the degradable environmental and bio-sensors, subject to final approval by the project sponsor. Your tasks Development of the project tasks and milestones
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/m/d) Development of soft-sensors connected to particlebased separation models to control flotation processes. Your tasks Develop and implement soft‑sensor concepts for continuous monitoring of ore
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Bonn, Medical / Mathematical and Natural Sciences Faculties; German Center for Neurodegenerative Diseases (DZNE) Description: The Research Training Group (RTG) “Development and epileptogenesis
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Description For our location in Hamburg we are seeking: PhD Position: Method Development for Hierarchical X-Ray Imaging at Synchrotron Facilities Limited: 2 years | Starting date: earliest possible
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looking for a PhD Student (f/m/d) to work on the Development and Evaluation of PET Image Reconstruction Methods for Simultaneous Clinical Dual-Tracer PET Imaging. Positron emission tomography (PET) is a
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PhD Position – High-Temperature Electrolysis – from stack design to operational optimizationFull PhD
cells with improved energy and power density, longer lifetime, and maximal safety. Find out more about our mission and future-oriented projects here: https://www.fz-juelich.de/en/iet/iet-1 We
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with upcoming tasks and (on‑site) appointments VACATION: You will receive 30 days of vacation KNOWLEDGE & DEVELOPMENT: Your professional development is important to us – we support you specifically and
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about the ISSE Institute, please visit our website: https://www.isse.tu-clausthal.de Your responsibilities include: Research and development in the field of software engineering for dependable and safe
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additional professor plus an international tutor of the RTG Description of the PhD topic: This PhD project focuses on the development of fail-safe, distributed digital twins (DTs) for urban air mobility
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data