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of health activism, health work, or health policy Willingness to learn oral history or ethnographic methods. Willingness to produce both academic and non-academic research outputs Downloading a copy of our
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analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
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the possibility to work within a well-resourced learning community where the students are rigorously selected and highly motivated. This results in an unusually interactive and intellectually engaging
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of health activism, health work, or health policy Willingness to learn oral history or ethnographic methods. Willingness to produce both academic and non-academic research outputs Downloading a copy of our
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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Travel ” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in
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evidencing: which scientific discoveries are more impactful than others; whether public attitudes to science change over time; how the public learn and talk about science; how different target groups respond
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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no.: 4331 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary