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motivated team that values a good work-life balance, further development and consolidation of your individual professional and personal skills, seminars, workshops and e-learning opportunities for personal
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potential. As an ambitious research university, we stand for research-based learning approaches and a pronounced interdisciplinary orientation. We actively pursue international scientific cooperation in a
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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an internationally recognized neuroscientific research institute and dedicated to the research on learning and memory. Our research comprises all organizational levels of the brain – from molecular and
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the newly established research team for the ERC Advanced Grant project “Equilibrium Learning, Uncertainty, and Dynamics. (Please find a German version below the English text.) The Chair of Decision
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 7 days ago
design-build-test-learn cycle. Integrating concepts from bioprocess optimization with metabolic engineering strategies. Your qualification The candidates should have an excellent degree and/ or experience
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verification scalable and reliable. Learn more about logical zonotopes: [paper link ] | [talk link ]. You will conduct original research on logical zonotope based methods for model checking and digital circuit
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-party research funding are expected. We are particularly interested in a candidate in any field of economics who leverages state-of-the-art machine learning and causal inference methods to innovative
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into neuroendocrine output to instruct adaptive physiology and behavior. Conversely, we seek to understand how internal states shape our physiological responses to the same cues. Our research is based on the premise