3 PhD positions on Big Data applications for cardio care
3 PhD positions on Big Data applications for cardio care
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Job description
We seek excellent and motivated candidates for 3 PhD positions in a collaborative research project in the area of big data applications for cardiac care.
The STRAP project is 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'. Three PhD candidates will be hired at the Eindhoven University of Technology with an interest in developing and evaluating interactive applications to support patients to collect relevant data to support the early detection and prevention of secondary heart failure and to increase the efficiency in early diagnosis of heart disease. They will collaborate with two other PhD candidates working respectively at Erasmus University and Delft University of Technology, as well as with a range of SME's involved in the project.
More specifically the NWO-funded STRAP project shall develop a data collection platform integrating state of the art self-tracking technologies to enable patients:
a) To make measurements at home which would otherwise require visiting the clinic;
b) To collect longitudinal data pertaining to daily life activity, emotions, and other relevant aspects;
c) To ensure higher adherence in self-tracking through the application of behaviour change techniques and gamification.
We shall develop and evaluate novel diagnostic and prognosis methods in two trials, each addressing groups where improvements are readily obtainable and highly relevant:
a) For elderly heart patients, we strive to reduce re-hospitalization rates, currently leading to serious health deterioration and substantial costs;
b) For all comers at cardiac outpatient clinics, we strive to lower costs and improve the quality of diagnosing heart disease.
The mainstay of our two trials is two-fold:
a) 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.
b) Novel analysis and early diagnosis methods that rely on this heterogeneous data set.
The STRAP project is 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'. Three PhD candidates will be hired at the Eindhoven University of Technology with an interest in developing and evaluating interactive applications to support patients to collect relevant data to support the early detection and prevention of secondary heart failure and to increase the efficiency in early diagnosis of heart disease. They will collaborate with two other PhD candidates working respectively at Erasmus University and Delft University of Technology, as well as with a range of SME's involved in the project.
More specifically the NWO-funded STRAP project shall develop a data collection platform integrating state of the art self-tracking technologies to enable patients:
a) To make measurements at home which would otherwise require visiting the clinic;
b) To collect longitudinal data pertaining to daily life activity, emotions, and other relevant aspects;
c) To ensure higher adherence in self-tracking through the application of behaviour change techniques and gamification.
We shall develop and evaluate novel diagnostic and prognosis methods in two trials, each addressing groups where improvements are readily obtainable and highly relevant:
a) For elderly heart patients, we strive to reduce re-hospitalization rates, currently leading to serious health deterioration and substantial costs;
b) For all comers at cardiac outpatient clinics, we strive to lower costs and improve the quality of diagnosing heart disease.
The mainstay of our two trials is two-fold:
a) 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.
b) Novel analysis and early diagnosis methods that rely on this heterogeneous data set.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
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Eindhoven University of Technology (TU/e)
Requirements
The department of industrial design of the TU/e is looking to hire three PhD candidates to fit the profiles described below. Candidates should hold a master's degree in a corresponding area and have an interest in designing and evaluating relevant solutions in the healthcare domain.
Experience in relevant topics will be very much appreciated.
PhD-B. Excellent candidates with a masters' degree in an area relating to human-computer interaction and interaction design are invited to apply. A background in topics such as persuasive technology, artificial intelligence, recommender systems, and game design will be very much appreciated. A genuine interest to engage with people to understand their needs and their physical and social context, carry out co-design activities, and carry out evaluation work is expected. Among the three PhD candidates, this one is expected to lead user studies and take responsibility for the user experience design.
PhD-D shall focus on the data science challenges in this project, with an emphasis on data mining and AI. Candidates should possess relevant experience/background in these topics and should be eager to master contemporary languages for AI, app and back-end development. They should be capable and interested to work with data stewards of the participating consortium members to define data management requirements, taking into account relevant legislation and best practices with regards to privacy and security of sensitive data. Candidates should have an affinity with developing health and behaviour monitoring and feedback systems and in approaches such as experience sampling and gamification and addressing long-term user engagement aspects.
PhD- E shall focus on the longitudinal and unobtrusive collection of data at home. Candidates should have a master's degree with a high academic grade in electrical engineering, computer science, biomedical engineering, medical technology or related discipline. Experience on biomedical signal processing, sensing system and technology, machine learning / deep learning, or data analytics is preferred. The candidates should be highly motivated, rigorous, and disciplined when researching and developing systems or algorithms according to high-quality standards. Strong programming skills (for example, Python, Matlab or R) are required.
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.
Experience in relevant topics will be very much appreciated.
PhD-B. Excellent candidates with a masters' degree in an area relating to human-computer interaction and interaction design are invited to apply. A background in topics such as persuasive technology, artificial intelligence, recommender systems, and game design will be very much appreciated. A genuine interest to engage with people to understand their needs and their physical and social context, carry out co-design activities, and carry out evaluation work is expected. Among the three PhD candidates, this one is expected to lead user studies and take responsibility for the user experience design.
PhD-D shall focus on the data science challenges in this project, with an emphasis on data mining and AI. Candidates should possess relevant experience/background in these topics and should be eager to master contemporary languages for AI, app and back-end development. They should be capable and interested to work with data stewards of the participating consortium members to define data management requirements, taking into account relevant legislation and best practices with regards to privacy and security of sensitive data. Candidates should have an affinity with developing health and behaviour monitoring and feedback systems and in approaches such as experience sampling and gamification and addressing long-term user engagement aspects.
PhD- E shall focus on the longitudinal and unobtrusive collection of data at home. Candidates should have a master's degree with a high academic grade in electrical engineering, computer science, biomedical engineering, medical technology or related discipline. Experience on biomedical signal processing, sensing system and technology, machine learning / deep learning, or data analytics is preferred. The candidates should be highly motivated, rigorous, and disciplined when researching and developing systems or algorithms according to high-quality standards. Strong programming skills (for example, Python, Matlab or R) are required.
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.
Conditions of employment
- a full-time temporary appointment for a period of 4 years, with an intermediate evaluation after 9 months;
- a gross salary of € 2.325 euro per month in the first year and increasing up to € 2.972 euro gross per month in the fourth year (PhD-salary scale Collective labor Agreement Dutch Universities) on a full-time basis, plus 8% holiday allowance and 8,3% end of the year allowance.
- excellent employment conditions (including excellent sport facilities and child care).
