Job offer
Role details
Job location
Tech stack
Job description
Neonatal and Paediatric Intensive Care Units (NPICU) represent particularly sensitive acoustic environments where sound exposure can negatively impact the physiological and emotional development of young patients and contribute to professional fatigue among nursing staff. Despite growing awareness of these issues, current technological solutions focus primarily on measuring sound pressure levels in decibels, which are difficult for non-experts to interpret and fail to capture, even in decibel A, how sounds are actually perceived by humans in context.
This PhD position is part of the NWO-funded project "Auditory Footprints: A novel soundscape assessment platform for neonatal and paediatric ICUs, which aims to develop the first integrated technological solution that automatically evaluates the perceived quality of the NPICU sound environment and empowers nurses to actively mitigate indoor sound exposure.
This PhD research envisions the design of an NPICU Data Commons, a digital infrastructure empowering nurses, and potential other key stakeholders, to understand and actively shape their working environment through data. Rather than a traditional top-down monitoring system, this platform will enable continuous, nurse-driven investigation where data is collected, explored, and acted upon by and for the nurses themselves. While the platform revolves around soundscape data as its core focus, it will be designed to open up and encourage integration of other forms of contextual and behavioral data (e.g., activity patterns, workflow rhythms) that nurses identify as relevant to understanding their acoustic environment. This vision includes establishing appropriate data governance mechanisms that enable nurses to make informed decisions about data sharing, both within their professional community and potentially with researchers or hospital management. The goal is not simply to create another dashboard, but to facilitate a shift in how nurses can capture, explore, and intervene in their acoustic environment, positioning them as active investigators and designers of their workplace rather than passive recipients of noise measurements.
The research will follow an iterative research and development process characterized by deep, on-site engagement with NPICU nurses throughout all phases. The work begins by defining human-centered design requirements through data probes combined with qualitative research methods including observations, interviews, and user diaries to understand the user journey and establish how occurring sounds relate to nurses' contextual needs and workflows. Building on these insights, the candidate will co-create the platform prototype through participatory design sessions with nurses, integrating the computational models (developed by another PhD candidate working in parallel on sound modelling) with user experience requirements, while simultaneously collecting and analyzing behavioral data (e.g., activity levels and sleep patterns) and conducting iterative data reflections with stakeholders. This co-creation process will lead to an implementation and evaluation of a live prototype: a server-based, functional digital platform that integrates the soundscape assessment algorithms and can be tested both in controlled environments and in-situ within the actual NPICU context. The candidate will observe, capture and analyze how nurses respond to, appropriate, and potentially transform the platform in their daily practice, with each iteration informing the next phase of development and deepening our understanding of how data-centric tools can meaningfully support healthcare professionals in addressing complex environmental challenges.
This PhD project offers a unique opportunity to contribute to a pioneering interdisciplinary initiative. The candidate will collaborate with experts from academia, hospitals, and industry to create a solution that has direct societal impact for improving healthcare environments and outcomes., Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Requirements
- MSc Degree in Human-Computer Interaction, Industrial Design Engineering or related fields.
- Strong background in human-centered design and qualitative research methods.
- Experience with data-centric design approaches and data visualization.
- Proficiency in prototyping tools and methods (both digital and physical).
- Solid background in programming and experience with machine learning.
- Knowledge of participatory design and co-creation methodologies.
- Ability to learn independently and passion for research.
- Strong communication skills in English and Dutch.
- Team player, open to discussion and constructive criticism.
- Previous involvement in scientific research is a plus.
- Open-minded and excited for multidisciplinary input.
- Positive attitude to diverse approaches and inclusive behaviour.
- Interest in healthcare solutions is highly valued.
Benefits & conditions
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.