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advanced modelling approaches—such as finite element analysis —to capture the nonlinear, multi-physics nature of soft materials. By integrating experimental data and validating simulations, your work will
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the Division for Geomagnetism and Geospace, an internationally leading research environment with strong expertise in space physics, geomagnetism, and data analysis. This position is connected with the ERC
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a talented and highly motivated researcher to work at the forefront of exoplanet atmospheric science with JWST. The postdoc will be involved with the analysis and interpretation of JWST data (new data
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, chemical etching, or FIB milling is a strong advantage. Familiarity with optical setups for imaging or polarization-resolved analysis will be considered a significant plus. Responsibilities You will be part
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analysis. The successful candidates will work under the supervision of Associate Professors Carlos Azevedo and Ravi Seshadri. The Intelligent Transport Systems Section belongs to the Transportation Science
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to apply. Strong programming skills, expertise in spectroscopic data reduction and analysis, and a demonstrated ability to work independently and collaboratively are highly valued. Flexibility and self
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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the metabolism of gas fermenting microorganisms, with a focus on C1 metabolism. You will work independently on the development of high impact research projects. You will use state of the art equipment
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analysis, to optimize the use of process chemistry as well as additives in fuels and lubricants. This also relates to how droplets propagate into nature and how they may carry chemicals far from where
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electroluminescence and photoluminescence imaging, preferably daylight and field-based methods. Proven skills in data analysis, image processing and machine learning. Experience with PV performance modelling, power