14 algorithm-development-"University-of-Surrey" PhD scholarships at Linköping University
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations in electron dose and scan stability, microscopy
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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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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at the intersection of AI and advanced electron microscopy. The project focuses on developing novel self-supervised and physics-informed deep learning methods to restore and denoise Transmission
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of FADOS is to achieve targeted modification of semiconductor properties through electronic doping to control and modify their electronic characteristics. The project’s goal is to develop fundamental
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application! We are looking for a PhD student in theoretical physics with a focus on AI-assisted workflows and database development for materials property prediction. Your work assignments Your tasks will be
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electronic doping to control and modify their electronic characteristics. The project’s goal is to develop fundamental understanding and innovative fabrication processes to solve urgent problems in organic
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trustworthy, we facilitate large-scale and reliable use of AI across different industries. Your work assignments You will work at the intersection of machine learning, cybersecurity, and privacy, developing
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reliable use of AI across different industries. Your work assignments You will work at the intersection of machine learning, cybersecurity, and privacy, developing methods to make AI systems trustworthy