At this time, only applications from EU/Swiss students can be considered.
Description of the Scientific Environment
The Quality of Life technologies (QoL) lab at the Information Systems and Services Science of Center for Informatics (CUI) of the University of Geneva is looking for a motivated PhD candidate. PhD topic relates to research on Quality of Life assessment and improvement for healthy populations while leveraging current QoL lab expertise in computer science, specifically, in mobile communication and computing technologies.
Project Description
The thesis will focus on research on Quality of Life assessment and improvement for healthy populations – while leveraging current lab expertise in mobile communication and computing technologies. More specifically the thesis focus is on researching Risk Assessment Toolbox – a set of decision support algorithms and computational models that leverage personalized, longitudinal datasets about the individual’s lifestyle and, in context of the current evidence in medicine, are able to provide a likelihood of the user being diagnosed with a chronic disease in the future. Factors for risk assessment will be extracted after applying advanced statistical analysis and iterative development of data mining and machine learning-based algorithms to previously labelled electronic health records (EHR) of ageing populations in Denmark, Spain, and Switzerland, amongst the others. Additional datasets will be collected within the PhD project. Personalized wearable technologies and smartphone applications will be modelled as a basis for the user’s “lifestyle sensor.” The thesis research will employ user-centric design methods and rely on interdisciplinary collaboration (i.e., different experts within the project and different user groups). It will also leverage the mixed-methods (quantitative-qualitative) approaches. The thesis research will contribute to software being developed for the mQoL Living Lab (implying Android/iOS, Python, R, Kotlin, Java, etc., see high-level mQoL-Lab platform description at GitLab). The applicant should be comfortable using standard machine learning libraries (e.g., sk-learn, pandas, PyTorch, and TensorFlow/Keras) and data visualisation software (e.g., Plotly, Seaborn, Matplotlib). Additionally, the CUI has its own FacLab, with 3D printers, laser cutters, and other tools, which may be freely leveraged within the PhD project.
Principal supervisor is Professor Katarzyna Wac
Job description
The chosen PhD candidate will be hired on a 2-year renewable contract. The position has a maximum duration span of 5 years. The first year will be a trial period during which both parties can terminate the working agreement with a 3-month notice period.
The key tasks as a PhD student are to:
Formal Requirements
Applicants should hold an MSc degree in bioinformatics, computer science, or related fields with excellent results and excellent English skills. French is welcome, but not required. High individual grades for courses, projects, or theses within statistics, machine learning, data mining, computer networks, mobile/web technologies, or algorithmic programming are also welcome. As criteria for the assessment of the qualifications, emphasis will also be laid on previous publications (if any) and relevant work experience (if any).
At this time, only applications from EU/Swiss students can be considered.
Application Procedure
The application, in English, must be submitted electronically to Prof. Katarzyna Wac.
Application Elements
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
The main criterion for selection will be the applicant’s research potential and the skills mentioned above. The successful candidate will then be requested to formally apply for enrolment as a PhD student at University of Geneva – the PhD in Information Systems and Services Science (https://iss.unige.ch/studies/phd/).
The deadline for applications is 1 August 2020, 23:59 CET.
Questions
For specific information about the PhD position, please contact the principal supervisor Prof. Katarzyna Wac (katarzyna.wac@unige.ch)