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Field
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Center. DTU Biosustain utilizes these advances for microbial cell factory design to
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of Arts The Faculty of Arts is a large, dynamic faculty in the heart of the city of Groningen. It has more than 5000 students and 700 staff members, who are working at the frontiers of knowledge every day
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) out to 2050. Tasks include compiling big-data inputs, developing CNOSSOS-EU compliant simulations, validating predictions with field/lab measurements and mapping future hot-spots. Ideal profile: honours
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group specializes in experimental quantum technologies spanning quantum information processing, quantum communication, and precision sensing. In this PhD project, you will work at the forefront of solid
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery
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or unethical responses, can be manipulated into producing them when provided with a large enough number of well-crafted “in-context” examples. This raises critical questions: Why do AI models adapt so
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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hole or neutron star orbiting at a large distance from a ‘normal’ companion star. This is a very long-lived state which accounts for the vast majority of the millions of binary systems harbouring neutron
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase