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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position in Soccer Analytics The Algorithms and Visualization
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Behaviour in Turbulent Fluids through Analytical and Probabilistic Methods” (grant number 233216). The successful candidate will investigate both phenomenological and theoretical aspects of turbulent fluids
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engineering applications. Empa's Centre for X-ray Analytics develops X-ray analytical and imaging methods for understanding materials structure in material, life- and medical sciences. This is a joint PhD
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characterization techniques. Work with different analytics to identify and quantify pollutants in water and their degradation mechanisms. Investigate the stability of the materials after use and how to prolong
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analytical and problem-solving skills with high scientific curiosity. Ability to work independently and in a collaborative, interdisciplinary environment. Excellent communication skills in English (both
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will: Develop novel and robust catalytic materials for efficient removal of emerging contaminants in water. Learn and apply advanced materials characterization techniques. Work with different analytics
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-on experience with microbiological methods, material characterization, or polymer/ nanoparticle/ hydrogel synthesis. Strong analytical and problem-solving skills with high scientific curiosity. Ability to work
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microfluidic system for the detection of various relevant analytes in saliva. Sensors will be made of electrochemical cells and transistors on soft and flexible substrates. Their fabrication will be processed
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characterization. The experimental nature of the work requires a very high level of experimental skills, an analytical mindset for interpreting results, and the ability to design innovative experiments. You are a
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. Empa is a research institution of the ETH Domain. At Empa’s Centre for X-ray Analytics, we investigate bio-nano assemblies from lipid nanoparticles (LNPs) to polymer-based nanosystems using powerful