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PhD position within the visuAAL Marie SkƗodowska-Curie Innovative Training Network: Acceptance of artificial intelligence in health-related contexts


visuAAL Marie SkƗodowska-Curie Innovative Training Network

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Dr M Ziefle No more applications being accepted Funded PhD Project (Students Worldwide)

About the Project

visuAAL is a four-year (2020-2024) Marie Skłodowska-Curie Actions Innovative Training Network, funded by the European Union, that aims at bridging the knowledge gap between users’ requirements and the appropriate and secure use of video-based AAL technologies to deliver effective and supportive care to older adults managing their health and wellbeing.

visuAAL will seek to increase awareness and understanding of the context-specific ethical, legal, privacy and societal issues necessary to implement visual system across hospital, home and community settings, in a manner that protects and reassures users; outputs will stimulate the development of a new research perspective for constructively addressing privacy-aware video-based working solutions for assisted living.

visuAAL will provide a transdisciplinary and cross-sectoral combination of training, nonacademic placements, courses and workshops on scientific and complementary skills to 15 high achieving Early Stage Researchers (ESRs). These newly hired ESRs will contribute through their individual research projects to fulfil visuAAL's aims.

visuAAL brings together 5 universities:
• Chair of Communication Science, Human-Computer Interaction Center, RWTH Aachen University, Germany
• The Swedish Law and Informatics Research Institute (IRI), Stockholm University, Sweden
• The Trinity Centre for Practice and Healthcare Innovation, School of Nursing and Midwifery, Trinity College Dublin, Ireland
• Computer Vision Lab, TU Wien, Austria
• Department of Computing Technology, Universidad de Alicante, Spain (Project Coordinator)

This Consortium is complemented by 14 partner organizations from Austria, Germany, Ireland, Italy, Portugal, Spain, Sweden, and United Kingdom; that will contribute to the research and training activities.

For more information about visuAAL, see https://www.visuaal-itn.eu/
Project title:
Acceptance of artificial intelligence in health-related contexts
Objectives:
This thesis focuses on the perception and acceptance of intelligent solutions for supporting, on the one hand, people who suffer from chronic diseases as well as medical staff, on the other hand. Required and desired functions of the technologies will be explored depending on the respective context and user group. In addition to the investigation of acceptance, perceived benefits, perceived barriers, and usage conditions are examined for a broad spectrum of health settings.
Expected Results:
The dissertation will outline an acceptance cartography of intelligent technology that supports in care, detailing the most important benefits of technical support but also the critical aspects (privacy, dignity, and control), Specifically, not only patients but also care personnel is taken into account.
Supervisory Committee:
• Main Supervisor: Prof. Dr. Martina Ziefle (RWTH Aachen University)
• Second Supervisor: Prof M. Kampel (TU Wien, Austria)
• Co-Supervisor: Dr. Philipp Brauner (RWTH Aachen University)
• Advisor: Dr. Christian Möllering (Enervision GmbH)
Planned secondment(s):
• Secondment 1: University of Alicante (Supervisor M. Richart) M18 – M20, training and research on video-based AAL technologies
• Secondment 2: Enervision (Supervisor C. Möllering), M31-M33, training and research on video-based AAL technologies
Enrolment in Doctoral degree(s): Doctoral Programme in Communication Science, Humanities Department (Dr. phil.), RWTH Aachen University
How to apply?
Submit your application to https://www.visuaal-itn.eu/esr-vacancies. Please, ensure that you select vacancy number ESR 3.
Information:
For questions related to this project proposal, please contact [Email Address Removed]

For all other questions, please use the following email address, clearly indicating the visuAAL vacancy number ESR 2: [Email Address Removed]


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