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candidates to conduct research in the field of evidence synthesis. The projects will focus on the development of statistical methods for the synthesis of complex data. About the research group The new research
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systems. By combining microclimate modelling, remote sensing data, and data-driven methods, the results are integrated into a Digital Twin framework. The research will support predictive risk assessment and
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with human values, and safety in current language technologies. As NLP-based systems are increasingly deployed in society, there is a growing need for methods to understand and mitigate the ethical risks
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plan proposal for academic supervisor(s) The project description must describe the topic, research question, theoretical basis, and choice of method. In addition, you must provide information about your
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for the position. Preferred selection criteria Knowledge of digital assurance frameworks, verification methods, or formal modeling Familiarity with adaptive or machine learning/artificial intelligence systems
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physics-based models and data-driven methods, to support interpretable and robust testing of autonomous behavior. Application of formal methods and reasoning techniques to support safety arguments
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complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation
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of Norway, aims to develop an efficient and scalable microbial-based bioconversion process for poultry feathers into highly digestible protein product. The position involves training through formal courses
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the faculty during the first months of the appointment. The candidate is expected to complete a coursework component of 30 ECTS as part of the formal PhD training. Experience of terrestrial field work and
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4: “Creative Use of AI in Education ”. The candidate is expected to contribute to answering work package 4’s research questions by exploring how AI is, or can be, integrated into formal, non-formal