Disability rather than early death has become an increasingly large share of the global disease burden rising from 21% in 1990 to 34% in 2019. Non-communicable diseases (NCD), including cardiovascular diseases (such as heart attacks and stroke), cancers, chronic respiratory diseases (such as chronic obstructive pulmonary disease and asthma) and diabetes, account for 71% of the annual death toll.

Primary health care that delivers patient-centered services (asynchronous) is the best way to effectively manage risk factors and uncomplicated NCD*. An asynchronous model that empowers and engages patients in the management of their health and is built on patient selfefficacy. In such an asynchronous model, healthcare access moves from the clinic (systemcentric) into the patient's daily life and health management shifts from the clinician to the patient. Developing data-driven solutions to improve patient self-efficacy will be a core differentiator coming out of these projects.

Job Description

The Data Analytics group of the Jheronimus Academy of Data Science (JADS) runs several projects that deal with extramural care of patients with chronic, lifestyle related, diseases. These projects are usually part of larger (inter)national consortia where partners from different academic, medical, and industrial organizations work closely together on project goals in this context. An example of this is the European project IRHIS (see attachment). In IRHIS there is a vacancy for one PhD candidate. We are looking for a team player with a strong background in data science/engineering who is willing to collaborate in multi-disciplinary international teams.

Short description IRHIS project

IRHIS aims to establish the first EU-wide Advanced Remote Care Demonstration Chain. It is meant to collaboratively demonstrate and scale Advanced Remote Care Tech Champions across Less Developed Regions (LDR). IRHIS will for that purpose build 3 Interregional DemoScale Labs accelerating the upscale of advanced AI-powered MedTech across 3 of the most critical EU remote care areas: musculoskeletal rehabilitation, neurological disorder treatment, and critical patient conditions (ICU).

In practice, our consortium will demonstrate and scale 8 key technologies developed by innovative scale-up SMEs from several European countries. To ensure a user-centric approach of the development, more than 1000+ patients will be involved in testing and evaluation activities, collecting millions of big data entries.

Processing this data will enable robust AI & Machine Learning model developments to ensure market fit and adoption of the IRHIS technologies. Further, clinical relevance will be created throughout 2 years of continuous, parallel and iterative testing across the 3 DemoScale Labs backed by our 20 partners from 13 EU Regions. Our interregional leverage will thus lie in data, tech (integration), and patients.

Beyond technology deployment, our initiative seeks to consolidate the fragmented EU remote care innovation landscape, mobilizing crucial investments, fostering interoperability, and harnessing the potential of a rapidly evolving field that promises improved patient journeys, predictive rehabilitation, and transformative care solutions. IRHIS thus envisions the establishment of a dynamic EU-wide ecosystem, with a focus on empowering innovators from Less Developed Regions. We will conduct capacity building activities and grow a portfolio of innovative scale-up SMEs meant to become global leaders in their domain.

• A master's degree (or an equivalent university degree) in Data Science, Computer Science or Electrical Engineering.
• A research-oriented attitude.
• Ability to work in an interdisciplinary international team and interested in collaborating with industrial partners.
• Motivated to develop teaching skills and to coach students.
• Fluent in spoken and written English (C1 level).

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 you:

• 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.

About us

The Jheronimus Academy of Data Science (JADS) is a unique cooperation between Eindhoven university of technology and Tilburg university. At JADS, we believe that data science can provide answers to society's complex issues. We provide innovative educational programs, data science research, and support for business and society. With a team of lecturers, students, scientists and entrepreneurs - from a wide range of sectors and disciplines - we work on creating impact with data science. We do this by connecting people, sectors and industries: in the past 5 years we have been working with 300+ organizations on data-related projects. Our main drivers? Doing cool stuff that matters with data. Our location at the former monastery Mariënburg in Den Bosch houses a vibrant campus fully dedicated to data science. Via this link you can view a short tour around JADS. 

We believe that diversity broadens our research scope and enhances the quality of our education (Diversity and Inclusion at TU/e | Eindhoven University of Technology (tue.nl).

Curious to hear more about what it's like as a PhD candidate at TU/e? Please view the video.

Information

Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager Aarnout Brombacher, Professor in data analytics in healthcare, a.c.brombacher@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact HR@jads.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

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. You can apply until Monday, September 23rdth, 2024.

The first interviews are scheduled on Wednesday, October 2nd  and Friday, October 4th.
The second round of interviews is scheduled for Wednesday, October 9th.