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PhD on Mining Social Media for Cardio Care in Artificial Intelligence at Eindhoven University of Technology


A position for an excellent and motivated candidate for a PhD position in social media in relation to big data applications for cardiac care.

The PhD will be executed in the context of both the Eindhoven Engine https://eindhovenengine.nl/) , at the TU/e campus where cross disciplinary and cross sector (academia/industry) research is fostered, and the STRAP project, a collaboration between three leading Dutch universities and several partners from the public and private sector interested in healthcare, funded by the Dutch NWO program ‘Commit2Data’.

Within the STRAP project, this specific PhD shall examine the role social media can play to support the target patient group and how data from social media can be mined to support the prognosis methods developed by the project.

This PhD will work with a team of six PhD researchers in three Dutch universities (TU Eindhoven, TU Delft, and Erasmus MC) will work on developing and evaluating interactive applications to support prevention of secondary heart failure and to increase the efficiency in early diagnosis of heart disease. Accepted candidates will have a unique opportunity to position themselves in the forefront of future healthcare.

  1. To make measurements at home which would otherwise require visiting the clinic;
  1. To collect longitudinal data pertaining to daily life activity, emotions, and other relevant aspects;
  1. To ensure higher adherence in self-tracking through the application of behaviour change techniques and gamification.
  1. For elderly heart patients, we strive to reduce re-hospitalization rates, currently leading to serious health deterioration and substantial costs;
  1. For all comers at cardiac outpatient clinics, we strive to lower costs and improve the quality of diagnosing heart disease.
  1. A lasting and connectable data set for studying the performance of a variety of digitalized old and new techniques in relation to other health records. Our heterogeneous data set comprises of electrocardiography, audio files derived from stethoscopes, activity levels measurement from wrist-worn devices, data of an electronic nose, and self-report data and sensor data collected using IoT technologies, which pertain to water consumption, sleep patterns, experience sampling of feelings, physiological data relating to emotions (galvanic skin response and face expression recordings) and the well-being of the patient.
  1. Novel analysis and early diagnosis methods that rely on this heterogeneous data set.

Candidates should hold a masters’ degree in an area relating to humancomputer interaction, data mining or artificial intelligence. Candidates should be eager to master contemporary languages for AI, app and back-end development. A genuine interest to engage with people to understand their needs and their social context, carry out co-design activities, and carry out evaluation work is expected.

All candidates should be proficient in written and spoken English. Fluency and good command of the Dutch language will be very much valued in conducting research and design activities locally in which elderly cardiac patients can participate. Further, they are expected to be proactive in collaborating with other PhD students, colleagues and supervisors from a wide spectrum of backgrounds. Excellence of creativity, autonomy, and dedication are expected personal qualities. A genuine interest in research, familiarity with design thinking, experience with writing and publishing scientific research and experience in collaborative research projects will weigh positively. The candidates should have (and will develop further in this project) strong professional and communication skills in order to work together with remote partners in a multi-national and multi-disciplinary research team.

General information about TU/e and the Industrial Design Department, candidates will find on https://www.tue.nl/en/

Specific questions about the project can be addressed to Pr. Jun Hu (J.Hu) Pr. Panos Markopoulos (P.Markopoulos) and Dr. Daniel Tetteroo (D.Tetteroo).

If you have any questions about the application procedure, please contact HR Services Industrial Design, tel. +31(0)40 247 5336, email: HR-IndustrialDesign

For further details, please see: https://www.scholarsbase.com/t/phd-...ce-at-eindhoven-university-of-technology/2548

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