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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | about 5 hours 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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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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are offering four PhD positions in the Simulation and Data Lab Digital Bioeconomy (SDL-DBE). The SDL-DBE develops and applies multiscale models, AI-enhanced simulations, and computational workflows across IBG
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applications in information technology and are based on electrical, magnetic or optical functionalities. The Department of Quantum Technologies is looking for a PhD Student (f/m/d) - Imaging magnetic structures
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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processes that produce energy and raw materials. The Department of Structural Materials is looking for a PhD Student (f/m/d) in Ion Irradiation and Materials Characterization of Novel Refractory High-Entropy
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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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: Algebraic geometry and number theory Area 3: Stochastics and mathematical finance Area 4: Discrete mathematics and optimization Area 5: Discrete geometry Area 6: Numerical mathematics Area 7: Applied analysis
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interdisciplinary PhD projects in the Simulation and Data Lab Digital Bioeconomy. Each project combines natural sciences with computational and data-driven approaches, focusing on topics such as plant carbon