310 algorithm-development-"Multiple"-"Prof"-"Prof" uni jobs at University of Sheffield in United Kingdom
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year round Details This research is aimed at developing scalable Bayesian approaches able to solve complex and high dimensional problems with multiple objects and multi-sensor data. One such problem is
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programmes across discipline specific themes, in this case, Rail. You will look after multiple funded rail based research projects within the Tribology Research Group, having excellent interpersonal and
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experimental research as well as data analysis and algorithm development. Students with either an undergraduate honours degree (1st) or MSc (Merit or Distinction) in engineering, mathematics, neuroscience
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participate in developing algorithms for tau lepton identification, and will also have the opportunity to assist with silicon module construction for the ATLAS tracker upgrade. Instructions for applying can be
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Directly Funded UK Students Dr Jon Willmott, Dr Matthew Hobbs Application Deadline: 23 June 2025 Details The fusion energy sector must develop methods of remote maintenance where human access is impossible
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The development of flexible cognition in children and adults School of Psychology PhD Research Project Self Funded Dr D Carroll Application Deadline: Applications accepted all year round Details
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Development. You will also aid in the development of portfolio and finance processes to improve performance. Policy support and creation are a key aspect of the role within the portfolio and experience
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research project aiming to co-develop an intervention to improve care coordination for people with motor neuron disease. The post provides an excellent opportunity to undertake high quality research within a
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al. 2023). This study has not been performed in multi-dimensional simulations due to a lack of available simulation software. Ruan et al. (2020) developed the first beam-MHD hybrid model capable
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complex cytoplasmic networks. These networks span across multiple cells, providing structural rigidity and allowing tissues to withstand mechanical forces. Keratins are less studied compared to other