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knowledge areas include cyber-security, applied machine learning and data mining, intelligent video analytics, natural language processing and artificial intelligence, autonomous learning and dynamically
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genetic correlations, development and evaluation of polygenic scores, and integration of genomic predictors into multivariable and machine-learning prediction models for treatment outcome. Working closely
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turbines represented using an actuator-line approach, assess the applicability and limitations of reduced-order models in predicting turbine performance, and develop machine-learning surrogate models capable
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machine learning, spatial audio & audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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partners. Evidence of managing projects, risks and milestones using tools such as Gantt charts, risk registers and Git. Desirable Machine learning (time-series modelling, deep learning such as LSTM or CNN
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teaching, learning, and assessment across our Hair & Beauty curriculum. You will play a key role in ensuring learners receive an excellent educational experience, supporting their progression into employment
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London School of Economics and Political Science; | London, England | United Kingdom | about 1 month ago
management software and the ability to manage own areas of responsibility independently without constant direct supervision. Experience in Stata and Python is essential, and machine learning is desirable. We
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, with various start dates. If you have difficulty accessing a computer, please call 029 2087 6137. Benefits We offer a leading and rewarding staff benefits package: 32 days holiday per year plus 8 bank
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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future of formulated polymers. We are seeking a Research Fellow in Computational Chemistry and AI/Machine Learning to advance the state of the art in understanding the degradation and biodegradation