PhD Position in Epidemiology/Digital Health: Digital Follow-up of post-Sepsis (UMZH Learn4Sepsis) 80 %

Description du poste

### The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer! ### Your responsibilities This PhD project is embedded in Work Package 5 of the UMZH Learn4Sepsis project and aims to design and initi-ate a digital follow-up cohort of persons after sepsis. For this, we will co-create a set of minimal data items and patient-reported outcomes to describe post-sepsis on different health- and daily life domains. By refining existing tools, we will develop and release an adaptive survey (including voice input options) to pilot a scalable, longitu-dinal study into life after sepsis. The tasks of this PhD position are: * Co-designing a minimal dataset and patient-reported outcomes for post-Sepsis * Co-developing conceptual and technical elements for setting up the adaptive survey (Key elements: knowledge trees/ontologies, database systems, natural language processing) * Gathering and analyzing contextual and patient-reported outcome data (e.g. using - Developing and validating prediction algorithms using classical statistics and machine learning tools * (optional) Collection and analysis of wearable sensor data Your profile We are seeking a highly motivated candidate with: * A quantitative Master's degree (MSc or equivalent) in Statistics, Machine learning, Biomedical Sciences, Bioengi-neering, or a related field * Strong interest in person-centered health research and digital health technologies * Willingness to interact with stakeholders (patients, clinicians) * Some experience in information- and data management (experience with database systems, knowledge graphs are an asset) * Excellent programming or data science skills (R, Python), e.g. for time series analysis, machine learning methods for prediction * Experience in or willingness to acquire skills in Natural Language Processing * Excellent command of written and spoken English * Good communication skills in English (German is an asset) and capacity for interdisciplinary collaboration Applicants must fulfil eligibility criteria for Swiss-based PhD positions. Marco Kaufmann PhD program coordinator epibiostat-phd@ebpi.uzh.ch