212 machine-learning-"https:"-"https:"-"https:"-"Institut-Agro-Rennes-Angers" Fellowship positions in United Kingdom
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Field
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design and implementation of visual cues detection on video datasets (face and gesture), context-aware multimodal analysis, machine learning/self-supervised learning for automatically detecting subtle
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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unit and individual and collaborative research in the area of Power Electronic, Machine and Control. The role holder will be expected to conduct and lead high-caliber, impactful research at the forefront
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. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of speech, audio, time-series or signal processing is required. Ability
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degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image processing is required. Ability to effectively and efficiently utilise industry
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical
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processing and statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; Work on sleep datasets