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interdisciplinary environment within EMBRACER and international partners and apply advanced methods like Lagrangian tracking and reanalyses to reveal new insights into atmosphere-ice-ocean feedbacks in the Arctic
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and very good knowledge in quantitative and qualitative research methods Good knowledge of statistical software (e.g. SPSS or STATA or R or JASP) Strong commitment and the ability to work in a team
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Master in Experimental Psychology, HCI, UX or related fields Experience with research methods in social sciences (e.g., empirical research, experiment design) Experience in statistical methods is
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This PhD project will focus on developing AI-based methods to accelerate the Swansea University in-house discontinuous Galerkin (DG) finite element solver for the Boltzmann-BGK (BBGK) equation
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breeding and cultivation methods. Thus, we try to speed up the breeding of complex resilience traits for several crops in different growing systems. This collaborative effort involves four universities and
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, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding of the numerical methods behind CFD and turbulence
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), sustainable, and climate-adaptive crops. By combining plant biology, simulation modelling, and artificial intelligence we aim to develop smart breeding and cultivation methods. Thus, we try to speed up
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of the Dutch NWA consortium “PRELIFE”, https://www.originscenter.nl/prelife/ The origin of life remains one of science’s most profound and enduring mysteries. Despite numerous theories, no single explanation has
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explanations from machine learning models. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve using tools from
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-dependent source depletion. Reducing uncertainty in groundwater risk assessments through refined numerical methods. Applying the improved model to real-world groundwater contamination case studies. Career