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management scenarios using geophysics and numerical modeling. High-resolution subsoil characterization using electromagnetic induction (EMI), and ground penetrating radar (GPR) will be combined with soil
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activity and stochasticity). For example, localized dendritic activation underlies numerous computational functions across hierarchical levels, such as denoising (filtering), increased expressivity (tunable
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used to advance root phenotyping and soil functions. Soil-root interactions will be analyzed across management scenarios using geophysics and numerical modeling. High-resolution subsoil characterization
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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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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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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 14 days ago
carry out waveform development, and data analysis of gravitational waves observed by LIGO and Virgo detectors. Research topics and research environment PhD theses can cover a broad spectrum of topics in
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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regardless of their age and thus belongs to the 20 best universities in Germany, according to another recent analysis by Times Higher Education. Ulm University's subject range concentrates on the STEM fields
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profile Completed university studies (Master/Diploma) in the field of Physics (Computational-, Plasma Physics, Optics) or related field Mastery and use of the scientific method Experience in numerical
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distribution of subsurface heterogeneity to illuminate the imprint of past and present deformation. Project 2: Generation and analysis of a high-quality seismic catalogue in Greece and Albania with Deep Learning