CAREER

We continously look for eager students and graduates to join our team as a bachelor or master candidate, intern, or as senior researcher and PhD student.

Bachelor/Master Theses & Semester Projects

Master thesis: Dropout Prediction in Digital Health Interventions

#datascience #digitalhealth #machinelearning

Project context: Digital Health Interventions (DHIs) and, more specifically, mHealth apps show vast potential in supporting healthcare systems with the globally increasing prevalence and economic costs of chronic diseases – the leading causes of death and disability worldwide. However, despite the availability of evidence-based DHIs, a substantial proportion of users do not adhere to them, ultimately dropping out and thus not receiving treatment. To solve this problem, we collaborate with several project partners that develop and distribute mHealth apps targeting food literacy, substance use, high blood pressure, sleep hygiene, and diabetes. Analyzing real-life longitudinal data of their apps, we aim to identify factors influencing non-adherence and explore machine learning methods that can effectively predict dropouts. Further information can be found on the project website.

Candidate profile: We are searching for highly motivated, proactive, and self-directed students with a general interest in digital health. You should be proficient in creating clear and comprehensible R/Python scripts that can be reused by other parties to explore and analyze large datasets. You should have experience cleaning and organizing data and applying relevant statistical models. You will be fully supported as to relevant theory from medical and behavioral sciences and how to write your thesis for a healthcare audience.

Master thesis/internship tasks: You will clean, organize, and analyze given data sets, conduct statistical analysis, engineer and select feature variables, and explore machine learning methods that classify potential dropouts in mHealth apps. Your work will be part of a more extensive scientific study which is subject to being published in a renowned medical peer-reviewed journal, which you are invited to co-author based on your contribution. The project can be conducted entirely remotely. We highly encourage members of underrepresented groups to apply. Students from other universities than ETH Zurich are also welcome to apply.

Start: Anytime, as soon as possible

Methodology: Longitudinal data analysis

Duration: 6 months (or to be discussed)

Interested students are invited to send an email to Robert Jakob at rjakob@ethz.ch.

Master thesis/internship project: Passive mobile sensing in anxiety patients prior to and during cognitive behaviour therapy

Finishing your studies at the University of St. Gallen or ETH Zurich and looking for an exciting thesis matter? Why not considering one of these:

The Experimental Psychopathology and Psychotherapy group (Dual affiliation with the Psychiatric University Hospital and Dept of Psychology, UZH) offers an open master thesis project on passive sensing data collected through a mobile app within a randomized clinical trial on anxiety (SNSF OPTIMAX project, optimizing psychotherapy for anxiety disorders, headed by Prof. Dr Birgit Kleim). Passive sensing data was collected in collaboration with the group of Dr Tobias Kowatsch at the Centre for Digital Health Interventions, ETH Zurich and University of St.Gallen.

The OPTIMAX project aims at improving the treatment of anxiety disorders by establishing improved prediction models. Participants are patients with a primary diagnosis of anxiety and the treatment consists of 16 to 18 weeks of cognitive behavioural therapy. The aim of the master thesis is to investigate whether passive sensing data are feasible to describe different behavioural patterns in everyday life and whether these data can be used to predict treatment outcomes. Passive sensing data are collected pre, mid and post-treatment, therefore changes in the course of treatment can also be investigated.

Potential master candidates or interns should have an interest in digital assessments, data science and/or clinical psychology/psychiatry and, ideally, experience working with larger data sets. They will be supervised by the teams of Prof Kleim and Kowatsch.

Starting point: Immediate or upon agreement

If you are interested or need further information please email Dr Miriam Müller Bardorff via mmb@psychology.uzh.ch

Miriam Müller-Bardorff, PhD
Postdoctoral research scientist, clinical psychologist

Research and Software Engineering Positions

Already graduated, and looking for an opportunity to change the world, at least a little bit? Why not join us as a researcher:

PhD Position in Machine Learning for Predicting States of Receptivity in Digital Therapeutics (100%)

Job description

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 SingHealthSEC 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.

Project background

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.

Job description

As a PhD student, you will make prevention measurable, actionable, and accountable by developing effective digital therapeutics for healthy longevity. In particular, you will use intensive longitudinal behavioural and physiological data (e.g., smartphone sensor data streams) and work on a smartphone-based digital therapeutic that predicts states of receptivity, i.e., opportune moments when individuals are able to receive, process, and use support. To this end, your research will build upon our award-winning work (ACM IMWUT Distinguished Paper Award 2022) on states of receptivity (Kuenzler et al. 2019 and Mishra et al 2021). The resulting state of receptivity system will be used to trigger behavioural precision interventions that slow down biological ageing processes. MobileCoach (www.mobile-coach.eu) written in Java and Javascript (ReactNative), among other technologies, will be used for your thesis project.

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 Healthnpj Digital MedicineDigital 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 Java, Javascript (ReactNative), and mobile app programming (iOS and Android)
  • Familiarity with ethical, legal, and health-political challenges of medical research

We offer

  • 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 tkowatsch@ethz.ch (no applications)

Full Job Description

Apply online now

PhD Position in Machine Learning for Mental Healthy Longevity (100%)

Job description

As a PhD student, you will make prevention measurable, actionable, and accountable by developing digital biomarkers for healthy longevity. In particular, you will develop a digital biomarker for mental health and well-being by analyzing intensive longitudinal behavioural and physiological data (e.g. data from voice interactions, breathing patterns and other smartphone sensor data streams). Your activities will also build upon our current BEDDABreeze and CanRelax projects. The resulting digital biomarkers will be used to trigger behavioural precision interventions that slow down biological ageing processes. MobileCoach (www.mobile-coach.eu) written in Java and Javascript (ReactNative), among other technologies (Unity), will be used to conduct your digital biomarker research.

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 Healthnpj Digital MedicineDigital 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 Java, Javascript (ReactNative), and Unity
  • Familiarity with ethical, legal, and health-political challenges of medical research

We offer

  • a PhD position that allows you to contribute to the ongoing health challenges of our society
  • an interdisciplinary team of passionate resaerchers 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 www.c4dhi.org. 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 tkowatsch@ethz.ch (no applications).

Full Job Description

Apply online now

Research Assistant in Emerging Business Models in Digital Healthcare 

100%, CSS Health Lab

The CSS Health Lab is an integral part of the Centre for Digital Health Interventions (CDHI) (www.c4dhi.org), a joint initiative of the Institute of Technology Management at the University of St. Gallen (ITEM-HSG), the Department of Management, Technology, and Economics at ETH Zurich, and the Swiss health insurer CSS.

To qualify for this position you must be eligible for a PhD at the University of St. Gallen. You will work on specific projects in cooperation with our healthcare partner CSS. As part of our team, you take direct project responsibility. You will plan, conduct, and evaluate cutting-edge research at the intersection of the social, medical, and engineering sciences. This includes subfields such as entrepreneurship, general management, behavioural science, and information systems.

Employment conditions, compensation and benefits are attractive and based on the guidelines of HSG. The average duration necessary for successfully obtaining a PhD is 3 1/2 years.

What we are looking for:

  • A master’s degree in engineering, medical sciences, or social sciences with a GPA (Grade Point Average) of at least 5.0 (GPA of 2.0 and better in Germany and Austria) in combination with a strong interest in entrepreneurship and management.
  • Prior experience in applied research projects, start-ups, or venture capital, as well as prior work experience in the health industry, is advantageous
  • Strong interest in healthy longevity, social and health psychology, health economics, technology-based innovation
  • Self-confident appearance and high conceptual and communication skills, especially regarding presenting research results to a broad and interdisciplinary audience
  • Profound knowledge (written/oral) in German and English

If you are fascinated by the described task and would like to be part of a highly motivated, young team, we would be pleased to receive your electronic application directly to the lab’s scientific director and Assistant Professor for Digital Health at HSG, Dr. Tobias Kowatsch, tobias.kowatsch@unisg.ch, with the subject line: CSS Health Lab Application, Research Assistant, Emerging Business Models in Digital Healthcare. For further information please feel free to contact Dr. Kowatsch.

Job advert: CDHI-PhD Position-Emerging BM in digital Health

Other

You did not find anything suitable? Then don’t worry, we take unsolicited applications also from students abroad and other universities. Please check also the affiliated research initiatives and healthcare clubs:

Healthcare Club HSG

The Healthcare Club at the University of St. Gallen sees itself as a platform whose added value unfolds primarily in three dimensions:

  1. Knowledge Acquisition: Keywords like “Digital Health”, “Medtech” or “Hospital Management” have become more and more common recently, but don’t you really know what they mean? Or are you already well informed, but don’t really know how to get access to further knowledge? Through exclusive insights into the health sector, members will be able to gain valuable first-hand knowledge and experience.
  2. Interdisciplinary exchange: Would you like to share your interest in the healthcare sector, exchange ideas and have the opportunity to experience the views of students with a different background? Our aim is to stimulate professional discourse on current topics in the healthcare field. We create the space for discussions between students of different disciplines and, in the future, especially of the Joint Medical Masters.
  3. Networking: The Healthcare Club connects interested students with experts and partner companies who are specialized in the healthcare sector and thus aims to facilitate a career entry into the healthcare sector. Whether this takes the form of an internship or valuable advice from industry experts depends entirely on you. Benefit from the experience and network of those who are already there where you would like to go.
Auto-ID Lab

Whereas the global Auto-ID Labs Network with its Labs at MIT, ETH/HSG, Keio, Cambridge, Fudan, ICU (Korea), and Adelaide, is co-chaired by Prof. Sanjay Sarma, MIT, and Prof. Elgar Fleisch, ETH/HSG, the ETH/HSG Auto-ID Lab is currently run by its Assistant Director Asst.-Prof. Alexander Ilic. The St. Gallen / Zürich Auto-ID Labs research interests are centered on the Internet of Things in the retail industry, with a special focus on Radio-Frequency Identification (RFID) applications for the end-consumer, mobile phone applications, the extension of the Electronic Product Code (EPC) Architecture Framework for sensing capabilities, and technical approaches to combat counterfeiting. For more information please see www.autoidlabs.ch and www.autoidlabs.org.

Bits to Energy Lab

The Bits to Energy-Lab, co-chaired by Prof. Friedemann Mattern of ETH, and Prof. Elgar Fleisch of ETH/HSG has been established and run by Prof. Thorsten Staake, a former doctoral student of Elgar Fleisch. The lab is a joint initiative of several chairs and industry partners that is dedicated to investigating the role of ubiquitous computing technologies for sustainable development. Its research interests include the use of IT to reduce energy consumption and greenhouse gas emissions with a special focus on consumption visualization and carbon accounting. For more information please see www.bitstoenergy.ch.

Bosch IoT Lab

The “Bosch Internet of Things & Services Lab” (Bosch IoT Lab) is a joint initiative of Bosch Group and the University of St. Gallen (HSG). The lab’s mission is to find and test out business models for the Internet of Things & Services. In addition, researchers are working to develop innovative and breakthrough internet-based products and services. The first major areas of research include networked mobility and smart home. Prof. Elgar Fleisch chairs the initiative as the scientific head of the Bosch IoT Lab. The lab is operated under the direction of Assistant Professor Felix Wortmann (HSG). For more information please see www.iot-lab.ch.

Mobiliar Lab for Analytics

The Mobiliar Lab for Analytics is dedicated to investigating and improving human-machine interactions by the means of digital interventions and advanced analytics. It is a joint initiative of ETH Zurich and Mobiliar. The Lab seeks to understand when personalization can improve human-machine interactions, when digital interactions are preferable to personal interactions and what promotes trust in human-machine interactions. For more information please see www.mobiliarlab.ethz.ch.

Contact

If you have any open questions, please feel free to contact us.

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