PhD Position in Machine Learning for Predicting States of Receptivity in Digital Therapeutics (100%)
ETH Zurich is one of the leading universities of the world with a strong focus on science and engineering. In 2010 it established the Singapore-ETH Centre (SEC) in collaboration with the National Research Foundation (NRF) to do interdisciplinary research on pressing problems.
In collaboration with the National University of Singapore (NUS), the Nanyang Technological University (NTU), Duke – NUS, the National Health Group (NHG), National University Health System (NUHS), and SingHealth, SEC is undertaking a research program on “Future Health Technologies FHT“. It addresses some immanent health challenges by developing a future-oriented Mobile Digital Health Concept that tackles the increase in patients suffering from chronic diseases such as diabetes, obesity and stroke, as a consequence of a rapidly ageing population with mobile digital technologies, covering the value chain from acute care to patient’s private homes. Within this framework we are announcing the following job opening: PhD Position in Machine Learning for Predicting States of Receptivity in Digital Therapeutics, 100%, Singapore, fixed-term.
Healthcare systems worldwide face challenges arising from the increase in non-communicable diseases (NCDs), such as cardiovascular disease or mental disorders, their related risk factors, and associated economic costs. A holistic intervention paradigm focusing on physical, mental, and social health is needed to prevent and manage NCDs effectively. However, current interventions are limited in scalability and do not provide data-driven, precise, and actionable interventions. To this end, the Mobile Health Interventions module of the FHT program investigates how ubiquitous technology can be leveraged to support individuals at risk in the most scalable way. This is done by detecting vulnerable states and delivering high precision and actionable interventions, for example, with the help of digital biomarkers, smartphones, wearables, chatbots, or voice assistants.
You will work in a highly interdisciplinary team at the intersection of computer science, behavioural medicine, clinical psychology, and business innovation. You will also engage in promotional activities to increase community awareness of your digital biomarker research through conferences, workshops, keynotes, seminars, and social media engagement, while also working on grant proposals, study protocols and publications for high-quality, peer-reviewed journals (e.g., Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Lancet Digital Health, npj Digital Medicine, Digital Biomarkers).
You will have
- A Master’s degree in computer science, machine learning, statistics or related fields
- Programming experience
- Positive experiences with interdisciplinary collaborations
- Strong verbal and written communication skills in English
- Scientific curiosity and motivation to perform scientifically rigorous experimental work
The following competence would be advantageous
- Familiarity with ethical, legal, and health-political challenges of medical research
- a PhD position that allows you to contribute to the ongoing health challenges of our society
- an interdisciplinary team of passionate researchers working at the intersection of digital health technology and disease prevention
- exciting professional development opportunities
- access to a global network of digital health enthusiasts
- opportunities to present your research to local and international audiences
Are you Interested?
We look forward to receiving your online application including the following documents:
- Cover letter outlining your motivation and experience in the field
- CV including certificates (e.g. Master’s and/or Bachelor’s degree)
- An example of academic writing (e.g., your Master’s thesis).
- List of data science projects with code examples (e.g. link to a code repository)
- Transcript of records
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
For further information about our research and projects, please visit our website. More information about the Mobile Health Intervention Module of the FHT programme is available here: www.fht.ethz.ch/research/mobile-health-interventions. Questions regarding the position should be directed to Prof. Dr Tobias Kowatsch at email@example.com (no applications)
Full Job Description
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