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personalized mentorship from experienced professionals to accelerate your growth Collaboration. Work in an open environment that allows you to collaborate with multiple teams and get exposure to different groups
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. The research group led by Martin Enge is specialized in methodology-driven analysis of patient data, especially in the field of single-cell multiomics. We are a multidisciplinary group with expertise in both dry
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at the Faculty of Mathematics at TUD. Tasks: generation of hyper uniform patterns (point, scalar and vector fields) application of topological data analysis tools such as persistent homology and graph statistics
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students and senior researchers from multiple disciplines to tackle challenges in sustainable aluminium through AI-driven microstructural analysis. The NEST-WISE project offers a vibrant collaborative
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framework to enable meta-analysis of multiple large biobank datasets, all of this with the aim of increasing our sensitivity to unravel the complex genetic causes of disease and, in so doing, identify new
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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, optimization techniques, and climate change scenario analysis. The successful candidate will contribute to the development of intelligent models and decision-support tools that enhance the performance
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the right one for you! This is a fully funded PhD position to develop micromechanical models of high-pressure die-cast aluminium, a unique opportunity for a motivated individual to work in a collaborative
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and administrative duties. Requirements: very good university degree in mathematics, preferably with a focus on probability theory or analysis; curiosity and strong interest in rigorous, methodical