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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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quality of after-school care using existing, large datasets. The data includes: questionnaires for managers and caregivers; (coded) observational data; (coded) video data of interactions between staff and
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“The Collective Bystander”, led by Professor Marie Rosenkrantz Lindegaard, that aims to understand why bystanders take collective action in real-life emergencies. The project utilizes state-of-the-art video
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of the application deadline. Shortlisted candidates will be invited to participate in brief video interviews. Those advancing to the second round will attend either an in-person interview or an extended video call
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at TU/e? Please view the video . Are you inspired and would like to know more about working at TU/e? Please visit our career page. Website for additional job details https://www.academictransfer.com
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view the video . Are you inspired and would like to know more about working at TU/e? Please visit our career page. Website for additional job details https://www.academictransfer.com/356755/ Work
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process or the conditions of employment . You can also contact HR Services (hrservices.apse@tue.nl ). Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video . Are you
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analysis of experimental data, Matlab/Python coding. We look forward to receiving your application. Closing date is January 10th, 2025, but we will screen applications as we receive them. Promising
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the conditions of employment . You can also contact Leo van Houten, HR-Advisor, l.v.houten@tue.nl or +31 40 247 8269. Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video
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Sanchez, HR advisor, s.j.m.g.sanchez.van.oort@tue.nl . Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video . Are you inspired and would like to know more about