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-funded project led by Dr. Jagmohan Chauhan in an exciting area of embedded machine learning. The post will be based at the University of Southampton. You will be working with Dr. Jagmohan Chauhan (PI), a
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computer vision is required. Experience of efficient ML techniques, edge AI hardware platforms, low-power computing, earth observation is desirable. They will have excellent programming skills (Python, C
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listeners. We are seeking candidates with a Ph.D. (either awarded or nearing completion) or equivalent professional qualification and experience in Machine Learning, Statistics, or a related field, who have
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term basis for 36 months due to funding restrictions. As part of your role, you will: Develop novel Bayesian machine learning approaches for psychoacoustic modelling. Publish your findings at top-tier
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post for a post doc/research software engineer to work on EPSRC grant EP/W030756/2: “aeon: a toolkit for machine learning with time series”. aeon is an easy-to-use, scikit-learn compatible toolkit for a
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analysis, human centric artificial intelligence, machine learning or large data management. We are seeking candidates whose expertise spans these backgrounds with a track record and demonstrated curiosity
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with a global sediment database and use remotely sensed and other geographical data with machine learning/Bayesian Modelling techniques to establish drivers of global sediment flux. They will use
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performance. Most recently, we have used existing data to train machine learning/AI algorithms to mirror the multidisciplinary team (MDT) process that determines the course of treatment for patients, as a first
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strategic investment by UKRI, and part of the School of Electronics and Computer Science. The role will involve a core focus on AI research (machine learning, multi-agent systems, causal AI, optimisation
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data analysis and machine learning skills. The Research Fellow in Intelligent & Resilient Ocean Engineering – Geoscience will join a large community of scholars at Southampton working across the marine