PhD on long-term monitoring of sleep disorder symptoms with digital tools

The mission of the Department of Electrical Engineering is to acquire share and transfer knowledge and understanding in the whole field of Electrical Engineering through education research and valorization. We work towards a Smart Sustainable Society a Connected World and a healthy humanity (Care & Cure). Activities share an application-oriented character a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Introduction

Are you eager to work on digital monitoring tools and data science for medical applications Are you fascinated about sleep In this project TU/e works together with Sleep Center Kempenhaeghe and Takeda to improve long-term low-obtrusive monitoring of the sleep disorder narcolepsy and facilitate management of daytime complaints using digital health technology.

Job Description

Narcolepsy is a chronic sleep disorder that typically imposes a substantial burden on those affected. People with narcolepsy often experience a broad range of symptoms such as excessive daytime sleepiness cataplexy hypnagogic hallucinations sleep paralysis and fragmented nocturnal sleep. Moreover the spectrum of narcolepsy also includes symptoms that manifest more during daytime such as automatic behavior cognitive impairments or mood disturbances. Symptoms greatly vary among patients and day-to-day variance can be considerable. Available narcolepsy questionnaires do not cover the full symptom spectrum and do not - or only retrospectively - capture symptom variability. Therefore there is a clinical need for tools to monitor narcolepsy-related symptoms over time to assess describe and predict the associated burden in daily life and evaluate the effect of treatment on everyday behaviors and experiences during sleep and wake.

M-Health offers the opportunity to monitor user experiences during their daily routine over prolonged time in a scalable manner. Sleep Medicine Center Kempenhaeghe developed the Narcolepsy Monitor a digital research tool to gain insight into both the individual and synergetic burden of 20 narcolepsy symptoms over this project we aim to detailly expand our knowledge of the narcolepsy symptom spectrum gain a better understanding of the inter-relation between patients symptoms and lived experiences and advance longitudinal monitoring of disease burden. A better understanding of the symptoms and their dynamics over time as well as interindividual variability in the ecologies of specific symptoms can help to tailor treatment to the individual patient.

To facilitate the monitoring of narcolepsy-related symptoms with an m-Health application it is important to understand which symptoms should be logged and with which frequency to map and better understand patients lived experiences. Moreover to mitigate user burden monitoring should occur as minimally obtrusive and as engaging for a large audience as possible. Unobtrusive sensor technologies could complement self-reported data and may reduce the sampling frequency of self-reports.

The current project has three main aims contributing to monitoring narcolepsy with an mHealth application:

• Analyzing the Narcolepsy Monitor database to identify symptom clusters and to quantify dynamics of longitudinal disease burden. We will investigate associations between symptoms experienced by narcolepsy patients and assess temporal dynamics in the symptoms from a 24/7 perspective. To this end we will analyze variations in symptom severity within days across days weeks and explore variance over longer timeframes such as months. This will help us learn about which symptoms to monitor and at what time resolution.
• Advancing insights about the integration of sensor data by analyzing self-reported data augmented with wearable data obtained through a new data collection campaign.
• Understanding patients and healthcare professionals preferences in patient monitoring and co-creating and analyzing dashboards tailored to the needs of the different user groups (patients and healthcare professionals).

In this project you will work in a multidisciplinary team which combines expertise on sleep medicine in general and narcolepsy in particular together with longitudinal monitoring and digital health technology. This research will be conducted in both the Advanced Sleep Monitoring research group (Biomedical Diagnostics lab Electrical Engineering) and the Human Technology interaction group (Industrial Engineering & Innovation Sciences) at the TU/e. You will work in close collaboration with Takeda and Sleep Medicine Center Kempenhaeghe. Kempenhaeghe is a tertiary expertise center for sleep medicine with specific experience with diagnosis and treatment of narcolepsy patients. Takeda is an international pharmaceutical company which has a narcolepsy medication in development.

Job Requirements

• A masters degree (or an equivalent university degree)in data science human-technology interaction neuroscience technical medicine or psychology (or related fields).
• Experience with advanced statistical modelling
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with clinical and industrial partners.
• Experience with (clinical) data collection
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).
• Fluent in spoken Dutch (required for interaction with patients and clinical staff during data collection campaign)

Conditions of Employment

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 addition we offer you:

• Full-time employment for four years with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks with a maximum of 15% per year of your employment.
• 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. 3059 - max. 3881).
• 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 childrens 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.

Information

Do you recognize yourself in this profile and would you like to know more Please contact the hiring manager Merel van Gilst ().

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services EE ().

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Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.