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Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about experimental aerodynamics and flow visualization? Apply for a PhD position
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Are you passionate about experimental aerodynamics and flow visualization? Apply for a PhD position that aims at transforming flow field measurements into aerodynamic forces by pressure and friction
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unsolicited services. Where to apply Website https://www.academictransfer.com/en/jobs/363304/postdoc-experimental-study-of-i… Requirements Additional Information Website for additional job details https
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Contrails are aviation sector’s invisible climate threats with large uncertainties. You’ll investigate contrail formation pathways for various particles through lab experiments. Job description Facing the climate crisis, the aviation industry has developed an ambitious “net-zero” goal to...
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project, you will develop and validate experimental methods to study wafer bonding in a quantitative and physics-based way. You will work on wafer bonding measurements and combine these with advanced
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: Develop AI-assisted experimental workflows for oxide semiconductor deposition, aiming to accelerate process optimization and unravel new process–property relationships, and contributing to an EU Horizon
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technologically relevant problem. Project goal The project aims to develop a predictive, experimentally grounded understanding of how rapid solidification and ambient pressure shape molten-tin droplet impacts, and
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and uncertainty in downstream predictions; fine-tune ARCA for tasks including microbial root competence and crop-relevant outcomes, and iteratively improve the model using experimental Design-Build-Test
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and photosynthesis. Your research is expected to deliver fundamental insights into the genetic regulation of tomato gene expression and provide strong experimental validation of the technology platform
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uncertainty in downstream predictions; • fine-tune ARCA for tasks including microbial root competence and crop-relevant outcomes, and iteratively improve the model using experimental Design-Build-Test-Learn