684 applied-physics-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Netherlands
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. To address this challenge, the project aims to develop structural health monitoring technologies based on a digital twin. The digital twin will combine information from the physical structure with models and
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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technologies based on a digital twin. The digital twin will combine information from the physical structure with models and monitoring data to assess its current structural state and predict its remaining
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level. As part of the ESA project team, you will support the execution and monitoring of the LSTM space segment development, with a particular focus on satellite engineering, industrial coordination
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, within the Systems Department of the Directorate of Technology, Engineering and Quality. You will work within a transversal team providing FDIR expertise across all ESA missions and directorates, covering
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Applied Physics, Electrical Engineering, or the equivalent. The PhD position is firmly imbedded in a physics environment, but the candidate strongly interacts with partners in applied physics, applied
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governance bodies, including preparation of decision proposals 8. Change Leadership and Adoption Support Co-lead, with the CFO Directorate, the digital and process-related organisational change associated with
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2026 Apply now Interested in how geospatial data science and GeoAI can be applied to investigate health system resilience under the rising pressure of polycrisis? Excited about developing spatial models
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quantum systems. Requirements You have a PhD degree in physics, applied physics, nanoelectronics or comparable discipline at the time of taking on the position. Prior experience in solid-state quantum
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, physics, applied mathematics, engineering, computer science or related discipline. Strong skills in fluid mechanics and numerical modelling. Experience with large observational data sets of environmental