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the start of the position Have practical experience in machine learning with Python, including training neural networks in PyTorch or a similar framework Have a solid background in signals and systems as
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and advanced machine learning. The project will integrate measurements from the SWOT satellite mission with Oxford's Global River Topology (GRIT) hydrography to develop verified, uncertainty-aware
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evidence to support the evaluation of AI and machine learning models. This may include investigating data-centric AI strategies, such as data quality assessment, annotation refinement, dataset curation, and
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, relating to craniofacial identification research and machine learning. You will require a computer science background. You will be applying AI and/or machine learning to Face Lab processes in relation
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contribute to the development and validation of computationally efficient motor-twin models for permanent magnet synchronous machines. The work will focus on machine modelling, parameter and state estimation
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unique experimental platform developed in the Bakshi Lab (https://www.bakshilab.net/ ) that enables time-resolved measurements of individual bacterial cells throughout the phage infection process. The post
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, Microelectronics, Computer Engineering, or a closely related field, completed by the start of the position Have a solid background in digital hardware design: Verilog/SystemVerilog RTL, logic synthesis, and place