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systems. Key Responsibilities Develop graph-based (multi-)omics analysis algorithms Benchmark graph-theoretic against graph-ML approaches Analysis of food-related (multi-)omics data Your Profile The ideal
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or functional properties. Collaborating closely with experimental partners to integrate decision-making algorithms into real scientific workflows. Publishing results in high-impact machine learning and
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data sets, which have to be evaluated in order to obtain a holistic understanding of very complex systems. Visit HDS-LEE at: https://www.hds-lee.de/ The position is placed at the Institute for Advanced
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Conduct comparative benchmarking and performance analysis against state-of-the-art studies Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate
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and AI algorithms Solid programming skills in Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience working with geospatial data (e.g., geopandas
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as of the 01.04.2026 at the following conditions: 50% = 19,92 hours Pay grade 13 TV-L limited by 31.03.2029 Your tasks: Development of architectures and algorithms for adaptation of time-triggered
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The LIT - Leibniz Institute for Immunotherapy (foundation under civil law) (https://lit.eu ) is a biomedical research center in the UNESCO-world heritage city of Regensburg. Our objective is to
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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in