687 machine-learning-phd "The Art Institutes" Fellowship research jobs in United Kingdom
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- https://www.kcl.ac.uk/jobs/088690-yeoh-tiong-lay-early-career-fellowship
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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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/6GIC), is looking to recruit a Research Fellow in applied adversarial machine learning. This exciting opportunity will contribute to the D-XPERT (AI-Based Recommender System for Smart Energy Saving
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Fellow in applied adversarial machine learning. This exciting opportunity will contribute to the D-XPERT (AI-Based Recommender System for Smart Energy Saving) project. The D-XPERT project represents a
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generation sequencing and microbiology. The successful candidate will work closely with an interdisciplinary team of academics at University of Nottingham. The role will include data analysis via machine
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machine learning, bioinformatics, sequencing and microbiology. This role is available on a fixed term basis until 31st May 2027. Hours of work are full time (36.25 hours). Job share arrangements may be
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takes input from a machine-learning platform (Python-based) to produce new compositions. A cobot delivers the material to the furnace or a plasma spray to produce new coatings. The proposed research is
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the power of machine learning, you will explore the interplay between metabolomic and proteomic data and depression to transform our understanding of this pervasive disorder. Based at King’s College London, a
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collaborators and travel to academic conferences and project meetings to present the work. Successful candidates must hold (or close to completing) a PhD in a relevant subject. Knowledge and experience in
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candidates must hold (or close to completing) a PhD in a relevant subject. Knowledge and experience in computer vision is required. Experience of efficient ML techniques, edge AI hardware platforms, low-power
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disease. This will involve data-driven feature extraction and the training and optimization of various machine learning models. The research will focus on analysing data from deeply phenotyped cohorts