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with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high
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-compliant data infrastructures that enable secure data sharing, reuse, and AI-driven analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical
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advanced machine learning and statistical methods, strong analytical skills and solid programming experience, very good English communication skills, both written and spoken, the ability to work
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spatial immune cell niches in cancer. Advances in high-throughput spatial omics technologies measuring various analytes now capture this complexity in remarkable detail, providing groundbreaking insights
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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language models, with hands-on experience in training, fine-tuning, or evaluating state-of-the-art models Solid knowledge in adversarial machine learning or trustworthy AI, including experience with
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for operational decision‑making, interactive design, or control‑in‑the‑loop visualisation. Machine‑learning surrogates offer speed, yet purely data‑driven models often extrapolate poorly and may violate physical
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Engineering, Mechatronics, or Robotics, with a heavy emphasis on dynamic system theory, or a closely related discipline. Strong academic background in applied intelligent control techniques, machine learning
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& Solar Power Plants Battery Energy Storage Systems (BESS) Smart Grids & Power Systems Sustainable buildings, communities and cities[EC1.1] Artificial Intelligence & Machine Learning for Energy Digital
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need to have a genuine interest in high-quality research and possess strong analytical skills with a scientific approach. As our activities are conducted in an international environment, you must have