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related research projects are possible. The first project studies information disclosure combined with mechanism design in markets with private information. The second studies dynamic information and
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
, satellite orbit determination, and HF engineering. Additionally, the group explores fundamental physics problems concerning small-scale ionospheric structures and non-linear radiation belt dynamics
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on sustainability, governance, mobilities, Arctic transformations, and societal change. The successful candidate will become part of a dynamic interdisciplinary environment, including UiT’s Environmental Humanities
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Job Description • Develop dynamic models and simulation frameworks for a novel pier-free telescopic coastal barrier system. • Design and implement coordinated control algorithms
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The Research Fellow (RF) will conduct research in the field of coastal dynamics, with a focus on the development and application of machine-learning-enhanced coastal models. The project aims
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for learning and sampling, temporal quantum information processing, non-Markovian dynamics, and quantum resource theories. The role also involves contributing to interdisciplinary research initiatives
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 months ago
molecules, is essential for anticipating target organs for metastatic spread, improving disease monitoring and timely treatment. However metastatic patterning is a highly dynamic process which even the most
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opportunity to learn from our highly interdisciplinary, collaborative, and dynamic research group that meets regularly and includes leading scientists (and other fellows) with expertise in several disciplines
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE