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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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available in standard Virtual Reality (VR) can be supplemented with speech recognition, natural language processing, and sentiment analysis. We aim to embody this potential in the front end of the Emote VR
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available in standard Virtual Reality (VR) can be supplemented with speech recognition, natural language processing, and sentiment analysis. We aim to embody this potential in the front end of the Emote VR
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multidisciplinary supervisory team spanning engineering, ecology, and environmental science, with access to state-of-the-art laboratories, field sensors, and data-analysis facilities. You will also join Manchester
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. You will gain expertise in experimental design, clinical research methods, data analysis, and science communication, working within state-of-the-art laboratories and with interdisciplinary collaborators
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focus on quantitative data collection, analysis and interpretation, alongside supporting the development of research proposals, ethics applications and dissemination of findings. You will work closely
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priorities Experience in developing and operating successful information analysis operations in an organisation of comparable size and complexity, including: Undertaking complex data gathering/information
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analysis, threat modelling, and proof-of-concept demonstrations, the research will identify and map vulnerabilities that may impact both individual investors and global financial stability, as
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. Project aims and objectives Aim: Develop methods for the analysis of ultrashort PFAS and use them to establish the risks from these emerging pollutants and the effectiveness of current remediation
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imaging, laser-Doppler imaging, transcranial Doppler ultrasonography, collecting/handling blood samples, and ex-vivo/in-vitro analysis of serum, plasma and monocytes. Good Clinical Practice certificate and