PhD Researcher - PDTx

Stroke remains a leading cause of disability worldwide. While improved early stroke response has reduced mortality, it has also led to a growing population of stroke survivors, increasing the demand for long-term rehabilitation and placing significant clinical and economic burden on healthcare systems. The current neurorehabilitation model relies heavily on resource-intensive, therapist-led care to meet the growing demand, underscoring the need for scalable, cost-effective solutions that extend into home settings. To address this gap, the first phase of the Future Health Technologies Programme (FHT1) at the Singapore-ETH Centre (SEC) (https://fht.ethz.ch)developed and piloted innovative upper limb rehabilitation technologies and evaluated them in a clinical context, both in the hospital and at the home of post-stroke subjects. Building on this progress, FHT2 seeks to scale up these technologies and conduct more extensive clinical evaluation to promote integration of technology-based clinic-to-home rehabilitation into Singapore’s healthcare system.

Specifically, one of our projects focuses on the development of a soft robotic hand orthosis to enhance upper limb rehabilitation sessions in the clinic and allow for additional task-oriented training at home. A first version of the soft exoskeleton has been developed within FHT1 and a proof-of-concept trial demonstrated preliminary feasibility, with post-stroke subjects using the rehabilitation device at home. However, adherence to home rehabilitation without therapist supervision and support can be challenging, ultimately affecting therapy dose. In this project, we will complement the exoskeleton with an AI-based digital health intervention, specifically an LLM-based conversational agent that will deliver support via a companion mobile app. The app will serve as both the user interface for daily interaction and support and a digital platform for data collection, remote monitoring, and telerehabilitation.

Within this PhD project, the objective will be to (i) derive the key requirements for the design of the digital platform and the LLM-based conversational agent (together with the input from end-users and building on pre-existing prototypes); (ii) iteratively develop the app and key interactive features (e.g., AI-based conversational agent, motivational interviewing, etc.) including their validation; (iii) interface the app with the soft hand exoskeleton technology (developed by another PhD student) (data transfer, data interpretation, feedback provision); and (iv) evaluate its impact on long-term adherence to a technology-supported rehabilitation intervention at home in the context of a 6-week proof of value clinical trial.

As a PhD researcher your work will focus on collecting evidence as well as clinicians’ and patients’ opinions to specify the required characteristics of the digital tool. You will then implement and develop the platform, connect it with the existing rehabilitation technologies developed within FHT2 before validating its impact through a clinical trial. The work will be performed in close collaboration with our research partners at Nanyang Technological University (NTU) and Tan Tock Seng Hospital (TTSH).

Your tasks will include:

• Getting familiar with the technologies developed within FHT, both in terms of rehabilitation technologies and previous digital interventions, and the evidence collected so far in our previous studies.
• Define the technical and functional requirements of the digital intervention (backend services, mobile app, infrastructure, etc.) based on literature as well as on clinicians’ and patients’ opinions.
• Develop and validate LLMs and/or ML models for increasing motivation and adherence to rehabilitation (e.g., using motivational interviewing strategies), while supporting and monitoring the outcomes of the behavioral interventions designed.
• Develop a cross-platform mobile application (mobile/web) and integrate it with the rehabilitation hardware developed at SEC, including data exchange, real-time communication, and backend infrastructure.
• Establish and validate a method to integrate the digital platform into the rehabilitation routine of patients and therapists.
• In close collaboration with local hospitals, plan and coordinate clinical studies with post-stroke subject to evaluate the digital platform, including the interaction with end-users.
• Collecting and analysing data.
• Tightly collaborating with a second PhD student developing the soft hand exoskeleton that will be used in the clinical studies.
• Contributing to the supervision of master students, technical staff, and internship students.
• Disseminating research outcomes at international conferences and in peer-reviewed journals.

• A Master’s degree in Computer Science, Software Engineering, Health Sciences and Technology, Information Systems, Informatics, or related fields.
• A strong interest in neurorehabilitation as well as in developing and applying digital tools in neurorehabilitation.
• Hands-on experience in machine learning techniques: theoretical foundations (e.g., model evaluation, data pipelines) and/or practical applications (e.g., training, fine-tuning, deploying models). Strong background in Python and experience with machine learning frameworks such as PyTorch or TensorFlow.
• Prior experience integrating LLMs into applications, including prompt engineering, API integration, or retrieval-augmented generation would be an advantage.
• Strong previous experience in app development, ideally in developing or prototyping mHealth applications.
• Experience with Python and JavaScript/Typescript, including frameworks such as React Native (frontend) and Django or FastAPI (backend). Familiarity with cloud platforms such as AWS for deployment is a plus.
• Strong interest in applied translational research and the direct clinical application of digital health technologies
• Motivation to work with clinicians and with post-stroke subjects
• Strong verbal and written communication skills in English
• Independence and “get things done mentality”
• Scientific curiosity and motivation to perform scientifically rigorous experimental work
• Desire to expand knowledge and acquire new expertise, work in an international environment

We seek candidates who take ownership of their research and are able to independently drive ideas forward. Successful applicants will actively engage with supervisors and collaborators, seek input when needed, and thoughtfully integrate feedback.

• Accredited with 5 Tripartite Standards by Tripartite Alliance for Fair & Progressive Employment Practices (TAFEP) Singapore.
• A diverse workplace with 32 nationalities, offering ample opportunities for mutual learning.
• Positive and inclusive working environment.
• 25 days of annual leave for fixed-term contracts.
• 1 day of Birthday Leave.
• Annual dental benefits.
• Committed to being a supportive employer as you prioritize your physical and mental wellness.
• Comprehensive healthcare insurance coverage.
• Flexible hybrid work arrangement (up to 2 days per week from home).
• Abundant networking opportunities across various disciplines.
• Accredited with NS mark certification.

The Singapore-ETH Centre is an equal opportunity and family-friendly employer. All candidates will be evaluated on their merits and qualifications, without regards to gender, race, age or religion.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.