As part of the PROMISE project, I look for a talented PhD candidate!
With the increase in aging populations and cancer incidence worldwide, the accessibility of cancer care is under high pressure. The higher number of patients requiring cancer care will receive that care from a decreasing number of healthcare workers: the double aging phenomenon. These patients are typically followed up in surveillance protocols for many years after their primary care, impacting their lives and healthcare accessibility. Fundamental action must be taken to adapt healthcare systems to be future-proof. This begs the question of whether an (intensive) in-hospital postoperative surveillance strategy is still warranted from a patient’s well-being and a societal healthcare cost perspective.
An optimal follow-up program for cancer (CRC) patients should be patient-centered, adaptive to patients’ needs, and measure objective and subjective cancer-specific and general health. Smart measurement technologies such as smart eHealth are essential in allowing adequate monitoring of patients’ well-being in the comfort of their homes. TU Delft collaborates with Erasmus MC to address this challenge by combining engineering and medical perspectives through two Ph.D. positions.
The objective of this Ph.D. project hosted by the TU Delft is the design, development, and study of methods and tools that enable data-centric, human-centered feedback mechanisms for cancer patients living at home. In this context, a feedback mechanism might involve the collection, detection, recommendation, and supervision stages. Data sources will include EORTC QoL Questionnaires, biosensors, general health data, and blood test results but might be expended as requirements and needs are refined.
Funded by the Dutch Cancer Foundation (KWF) and in collaboration with LifeSignals, Digitaal Verbonden, and Microsoft, the project will involve activities such as
- Technical Exploration of existing datasets to understand what is achievable (feasibility).
- Qualitative research with patients and clinicians to better understand what to achieve (desirability, viability), such as data probes and participatory data analysis.
- Functional implementations of the feedback mechanism with a Wizard-of-Oz approach.
- An autonomous implementation of the feedback mechanism (which might include human-in-the-loop, depending on the requirements).
We are looking for a person with an aptitude for independent creative work, good team working skills, and excellent English language skills. In addition, the candidate has a master’s degree in computer science, HCI, or related discipline, experience in machine learning and user studies, and an interest in design research in the medical field.
Ideally, the candidate should have experience with prototyping interactive systems and the medical context and the confidence to interact in Dutch with study participants.
For more information and application, check out our the TU Delft website.