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Field
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, programming, algorithms, and data analysis skills Outstanding research skills Applicants with Master degrees by research with technical publications and research experiences in structural dynamics and
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within the Reproductive Genetics team, with a specific focus on understanding the origins and consequences of embryonic aneuploidy. Your job Clinical duties will account for 30% of your time and include
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aims and objectives This project aims to develop an optimised, fault-tolerant implementation of the Falcon post-quantum digital signature algorithm for spaceborne FPGAs/processors. The key objectives
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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rewiring in glioma. We will leverage our expertise in genetic engineering and m6A profiling, and characterize the specific metabolome and lipidome composition of glioma. We will assess the impact of m6A
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algorithms, validated navigation architectures, and new insights into next-generation intelligent mobility solutions. The student will undertake two industry placements at Spirent, use high-tech simulation
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Project Background: Why some people with multiple sclerosis (MS) experience faster changes in brain structures (neurodegeneration) than others? What genetic associations with brain regional
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied