48 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at University of Sheffield in United Kingdom
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methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and academia. The candidate
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of dark matter particles in the decay of the gluinos. The search will be performed using the full ATLAS Run-3 13.6 TeV proton-proton collision data. The student will gain expertise in machine learning and
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survival is shaped by resource availability, competition, and cultural knowledge of food resources. You will work with an established bioacoustic dataset, a validated call machine-learning classifier, and a
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How does a molecule walk? Computer simulations of molecular machines in action School of Mathematical and Physical Sciences PhD Research Project Directly Funded UK Students Prof Sarah Harris, Dr
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develop our composite machining team. In this pivotal role, you will lead a diverse group of staff, fostering their skills in CNC programming and operation to efficiently undertake research relating
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with core data analysis and professional skills that are necessary for bioscience research and related non-academic careers. https://www.yorkshirebiosciencedtp.ac.uk Project Description: The highly
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for MND which could be translated into the clinic. The idea is to use cutting edge machine learning to create clinically actionable predictions such as the time from diagnosis to requirement for a
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“An improved machining temperature prediction model for aerospace alloys: Effect of cutting edge radius and tool wear”, Journal of Manufacturing Processes 133 (2025) 1100–1110. https://doi.org/10.1016/j.jmapro
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device health status through condition monitoring. AI techniques such as machine learning will be used to optimise gate driver performance and to map gate drive signal attributes to power device health
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. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies are planned. One will use a