PhD Researcher in Sleep Apnea Assessment from ECG
2 weken geleden
Are you passionate about signal processing and deep learning for medical applications? This project focuses on sleep apnea, a prevalent sleep disorder with significant cardiovascular implications. Our goal is to develop and validate novel algorithms for assessing sleep disordered breathing conditions using Holter ECG recordings.
Project OverviewThis project aims to further develop, optimize, and validate algorithms for sleep apnea detection using Holter ECG recordings in cardiac populations. The specific objectives are:
- Improve the diagnostic performance of ECG-based algorithms for sleep apnea detection.
- Extend the models' capabilities, ensuring robustness in the presence of arrhythmias, distinguishing between obstructive and central apnea, and uncovering sleep-stage-specific patterns.
- Investigate translating these algorithms to the Philips Holter recording device (e Patch) using clinical data collected throughout the project.
- Exploit the large Cardiologs Holter databases to study the relationship between cardiac conditions and sleep apnea.
The ideal candidate should have:
- A Master's Degree in Computer Science, Electrical or Biomedical Engineering or equivalent.
- A research-oriented attitude with a pro-active mindset.
- Able to interact in a multidisciplinary team including clinical and industrial stakeholders.
- Motivated to develop your teaching skills and coach students.
- Fluent in spoken and written English (C1 level).
- Ability to convey results in a clear and rigorous way, and interest in publishing.
- Strong experience in deep learning.
- Excellent coding skills in Python.
- Affinity with clinical topics.
The PhD student will be part of the Advanced Sleep Monitoring group at the department of Electrical Engineering of Eindhoven University of Technology and will closely work with Philips Cardiologs in Paris. The PhD will be based in Eindhoven, with the expectation to visit Philips Cardiologs office in Paris a few times per year.
You will work on a daily basis with Tom Mingasson, Fokke van Meulen, Nicola Pezzotti, Pedro Fonseca, and Sebastiaan Overeem.
We offer a meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer:
- Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
- Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,872 max. €3,670).
- A year-end bonus of 8.3% and annual vacation pay of 8%.
- High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
- An excellent technical infrastructure, on-campus children's day care and sports facilities.
- An allowance for commuting, working from home and internet costs.
- A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.
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PhD Researcher in Sleep Apnea Assessment from ECG
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Eindhoven, Noord-Brabant, Nederland Eindhoven University of Technology VoltijdJob DescriptionWe are seeking a highly motivated PhD researcher to join our Advanced Sleep Monitoring group at Eindhoven University of Technology. The successful candidate will work on developing and validating new algorithms to assess sleep disordered breathing conditions using Holter ECG recordings.Project OverviewThe project aims to improve the diagnostic...
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Eindhoven, Noord-Brabant, Nederland Eindhoven University of Technology VoltijdJob DescriptionWe are seeking a highly motivated PhD researcher to join our Advanced Sleep Monitoring group at Eindhoven University of Technology. The successful candidate will work on developing and validating new algorithms to assess sleep disordered breathing conditions using Holter ECG recordings.Project OverviewThe project aims to improve the diagnostic...
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