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significant experience in both theory and experiment. Please submit a curriculum vita and a list of publications. For full consideration, applications should be received by November 20, 2025. Interested
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periods as part of their training. CAMP is part of the Department of Economics which has a strong research-oriented faculty working within microeconomic theory, macroeconomics, econometrics, labour
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. Our work will be informed by sound theories and supported by empirical data. In this project, we will use AI as an opportunity and address the challenges that emerge due to AI. Our goal is to conduct
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to the Portuguese Labour Code and Decree-Law No. 57/2016, of August 29th, as amended by Law No. 57/2017, of July 19th. I. Admission Requirements Portuguese nationals, foreign and stateless persons may submit
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aims to develop and test fundamental theory in applied organisational research. It covers issues from the micro to the macro level of analysis. The programme has two “centres of gravity” that provide
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. This goal includes directions such as building hyperbolic vision transformers, making it possible to learn from multiple hierarchies, developing theory and implementations to make hyperbolic learning
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candidates with disabilities. If multiple candidates prove to be equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code IX (SGB IX) will receive priority
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | about 1 month ago
or equivalent) in Computer Science, Machine Learning or a related discipline. Strong foundation in machine learning / deep learning (theory + hands-on). Evidence may include a thesis, open-source project
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the Life-cycle – is a Marie Sklodowska-Curie Doctoral Network (MSCA-DN) funded under Horizon Europe. The project aims to train a new generation of researchers to advance rural development theory and practice
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Systems (MAS) theory: cooperation, negotiation, coordination, and competition. - Game theory and reinforcement learning for distributed optimization for agents' properties (e.g., perception, reasoning