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Field
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by cellular imaging using expansion and super-resolution microscopy. Your profile The candidate should have experience in state-of-the-art biophysical methods with a particular focus on the kinetic
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- Teaching courses and supervising of student theses YOUR PROFILE - University master's degree in geophysics or physics, above-average, with ideally good knowledge of seismic methods and numerical simulations
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involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can
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using a multiscale numerical approach, from atomistic to large-scale thermomechanical modeling, coupled with micromechanical experiments (see figure below). The master internship and PhD thesis will
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international research contexts Your Profile: Excellent Master’s degree in mechanical engineering, energy systems, computational engineering, or a related field Strong background in numerical methods and applied
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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modelling and numerical methods for ordinary and partial differential equations; Strong interest in working in a cross-disciplinary, collaborative project at the interface of electrochemistry and mathematical
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quantitative image analysis, numerical modeling, and explainable AI (XAI) with state-of-the-art biophysical methods. Using techniques such as traction force microscopy, microfluidics, 3D bioprinting, and
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sound, with human speech at the pinnacle of complexity. Like human babies, songbirds learn their vocalizations early in life from a social tutor. Numerous parallels to human speech learning, including
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methods: The Met Office aims to help its customers stay safe and thrive by producing reliable weather and climate information. Numerical models of the climate system are an important tool to help achieve