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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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pruning), carbon-aware computing, minimizing algorithmic complexity, maintenance requirements, mapping energy efficiency and related aspects using KPI (key performance indicators) with respect to ESG
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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transcriptomic technologies and biological data interpretation is a plus. Familiarity with optimizing cell segmentation algorithms for enhanced accuracy and efficiency, as well as experience with tools/packages
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and statistical subjects such as programming, algorithms, machine learning, and artificial intelligence. Define and supervise projects for Master and PhD students. Attract external funding from national
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algorithms and circuits to enhance imaging quality and speed Creating efficient data acquisition and processing workflows for large datasets of skin nanotexture images Optimizing hardware-software integration
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conditions for art and culture. Possible focal areas include AI and algorithmic creativity, digital media aesthetics, data-driven culture, new forms of the dissemination of art, literature, theatre and music
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sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued