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. Ability to develop, understand, and critically evaluate machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal
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of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied
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software developers to integrate data‑driven models with mechanistic or physics‑based models and domain expertise; showing thought leadership on applying data & AI-solutions in the food & biobased domain
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particular answer. A software application or data analysis project that you are proud of: what it does, what was challenging about it, and what your own contribution was. This may be a personal project
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progressive interfacial damage development as a function of fatigue loading. The models will be implemented and validated in commercial finite element (FE) software. The resulting FE model will define
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)medical or nutritional sciences.Preferably you have experience with working with large datasets in statistical software packages such as R, Python or SPSS. Proficiency in English at C1 level or higher (CEFR
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will be implemented and validated in commercial finite element (FE) software. The resulting FE model will define the digital twin of the welded structure and provide the basis for the second PhD project
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and Information Sciences (iCIS) at Radboud University in Nijmegen. iCIS conducts world-class research in machine learning, software science and digital security, and consistently ranks among the top
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damage development as a function of fatigue loading. The models will be implemented and validated in commercial finite element (FE) software. The resulting FE model will define the digital twin
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-speaking children and schools and communicating research findings internationally. You have experience with quantitative data analysis, preferably using tools such as R, Python, MATLAB, or similar software