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on real-life data from the maritime industry. As part of the PhD, you will be following advanced courses to extend your skills, implement and test algorithms, and learn to write scientific papers. As part
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. The candidate will design models and algorithms for learning and decision-making under uncertainty, optimized for real-time operation on heterogeneous physical devices. Finally, the position will address how
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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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algorithms aimed at predicting pathogen potential based on whole or partial genomes. You will also be responsible for integrating such tools into online accessible pipelines thus, providing the possibility
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that accounts for ion pairing in a consistent manner Apply the developed equation of state for different applications, including liquid-liquid equilibria, where a robust and sophisticated algorithm may need to be
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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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to the development of our algorithmic approaches and also contributes with the implementation of novel methods for the detection of cancer in tissues. Knowledge and in best case hands-on experience in handling images
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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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Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
performance and stability. You will work closely with modelling and reactor-focused colleagues to integrate evolutionary outcomes across scales. Your tasks will be: designing and running experimental evolution