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This PhD project will investigate partial differential equations arising from kinetic models, with a particular focus on variational methods. The research will explore how variational structures
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, the research will explore how populations change over time in response to ecological interactions, environmental variability, and other biological processes. The project aims to provide new theoretical insights
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patients. The effects on gene transcription, protein expression, cell morphology, ECM composition, and functional readouts such as diffusion and angiogenesis will all be explored. The model will provide a
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invisible and unnoticed. Existing approaches tend to overlook the role of the built environment and systemic social barriers as contributors to this problem. B4B integrates such perspectives and explores them
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electric machines for future defence and aerospace propulsion systems. The research will explore innovative machine topologies and advanced multi-physics design methodologies to enable electric machines with
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have the chance to explore basic machine learning research as well as more applied projects. While most of the work will involve technical machine learning research, you will also have access to clinical
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the Faculty of Psychology and Neuroscience (FPN) At FPN, we share a curiosity about the human brain and behavior. Together with our students, we explore how our brains function and learn why we do what
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its inverse reconstruction. A key challenge is the data-driven design of the experimental setup: exploring how the choice of measurements and configurations can be optimized to extract the most useful
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to continuously develop new skills, expand your expertise, and explore new areas of knowledge. Furthermore: You hold a Master’s degree in cognitive or computational neuroscience, artificial intelligence
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. Objectives: Develop mathematical models. Promote the communication and dissemination of the project results. Develop programming and data exploration techniques. 5. Applicable legislation and regulations