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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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objective of the project is to develop knowledge, models, and algorithms for physics‑informed autonomous control of heavy machinery in uneven and deformable terrain. Specific project tasks include fundamental
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are experts in systems science; we develop integrated solutions from care of the elderly to space robotics. We are now looking for a Postdoctoral researcher in quantum algorithms and optimization. Are you as
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new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. This role involves research and
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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for assisting the PI in the development and submission of data reports and presentations required by the funding agencies that sponsor/support research activities in the IMPACT Lab at JSNN. These reports require
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-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
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development, and algorithm implementation. A strong publication record in high-quality peer-reviewed journals and the ability to conduct independent, rigorous research. Excellent communication skills and the
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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Methods, LBM), and HPC. For a selection of possible research areas, see: https://www.math.cit.tum.de/math/forschung/gruppen/numerical-analysis/research/ Responsibilities: Development and analysis of new