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++) Knowledge of the fundamentals of ML/AI algorithms for communications and networking, and their implementation A creative mindset and curiosity to research and develop new solutions with highly skilled
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are to: Build a value chain decision-making tool based on mixed-integer linear programming Develop sensitivity and uncertainty assessment algorithms to assess various scenarios in a biofuel value chain Support
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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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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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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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with mathematical modeling and algorithmic insights Counterbalancing issues such as bias, overfitting, and inexplicable errors in excessive pre-training: by making systems explicitly aware of the reasons
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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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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