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


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 and

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

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

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


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