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Vacancies PhD position on the design and fabrication of MEMS drag force-based flow and fluid composition sensors Key takeaways In this project, we will combine well-known thermal flow sensing
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only advance fundamental science but also engage the public in the journey of discovery. In this specific project “Experimental Exploration of Protocell Formation on Early Earth” we will specifically
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model of human working memory. During the project, we will follow an intertwined model-experimental approach. First, we will use electroencephalography (EEG) experiments to investigate the neural basis
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mathematics, meteorology, geosciences or a related field; experience in climate modeling (considered an advantage); basic knowledge of (geophysical) fluid dynamics (considered an advantage); excellent skills in
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problem from various angles and disciplines basic knowledge of (geophysical) fluid dynamics; good writing and communication skills (English); experience with climate modelling or complexity science
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architectures, and on-device inference on edge-compute platforms. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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testing, to achieve sub-second cycle times for robotic systems. 3. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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, social engagement, and experimental practice. The project is embedded in a broader network of academic, artistic, and activist partners working across regions and disciplines. We encourage applications
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material models based on advanced ML methods, and to seamlessly integrate these models into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, thereby enhancing
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material models based on advanced ML methods, and to seamlessly integrate these models into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, thereby enhancing