PhD Student in Computer Science & Computational Modeling of Health Trajectories in Chronic Illness (Breast Cancer) *OPEN*

  • Listing number: UNIGE-2026-5
  • Publication date: May 20, 2026
  • Employer: University of Geneva, Switzerland
  • Workplace: Uni Battelle (Carouge)
  • Start: Upon Agreement, the latest: 1 January 2027
  • Employment: 75%-100%

At this time, only applications from EU/Swiss candidates can be considered. Application deadline: 2 July 2026 EOD.

Description of the Scientific Environment

The Quality of Life Technologies (QoL) lab at the Geneva School of Economics and Management Faculty (GSEM) and the Center for Informatics (CUI) of the University of Geneva is looking for a motivated junior scientist to join the lab (salary level: assistant A2, 75-100%). The lab research interests revolve around the fundamental and algorithmic problems, as well as human-centric challenges of the systems enabling an assessment and improvement of human behaviour, health, and quality of life in the long term.

Specifically, the research topic relates to research on Quality of Life assessment, modelling and its improvement for patients’ populations while leveraging current QoL lab expertise in mobile computing for data acquisition and expertise in machine learning, including deep learning for data modeling. The research will employ user-centric design methods, leveraging the mixed methods (quantitative-qualitative, in longitudinal, large scale data collection studies with patients) and rely on interdisciplinary collaboration for data collection and the derived models’ evaluation.

Research Context

Chronic illnesses as non-communicable diseases (NCDs) like cardiovascular, diabetes, pulmonary, cancer or neurological diseases have a profound impact on global health, with millions of new cases and a significant number of fatalities reported. Chronic diseases have a multitude of complex causes, with behavioral ones, like sedentarism, malnutrition, smoking, alcohol consumption, lack of sleep, and poor stress management, contributing up to 60% of the probability of its expression. Also, chronic diseases are now being diagnosed at earlier ages, than centuries ago. There is an urgency to address the challenges posed by chronic illnesses, not only from a healthcare perspective but also in terms of their broader societal and economic implications.

The life quality outcomes are increasingly researched as very important outcomes in chronic illness, as the disease symptoms may be debilitating, and the treatments are long and burdensome for the patients, who try to reconcile their personal, professional, social, and other activities with their health state. Currently, patients’ physical and psychological status and overall life quality (QoL) are typically assessed via Patient-Reported Outcomes (PROs). However, these assessments suffer from biases affecting reporting, ceiling and floor effects, and a lack of sensitivity to change at their scale’s extremes. Conversely, personal smartphones and wearables are becoming increasingly accurate in measuring short and long-term behavioral Technology-Reported Outcomes (TechROs). The extent to which TechROs provide complementary life quality information, which may be clinically useful, is being researched. To this end, this project we will focus on investigating the operational and human factors influencing the use of new technologies (wearables, apps) to collect quality of life (PRO/ HRQoL) datasets in clinical trials, research studies, and in routine clinical practice.

The project, in context of which the candidate is expected to lead the Swiss consortium efforts is the European Organisation for Research and Treatment of Cancer (EORTC) EMBED Research Project. The candidate is going to be mentored to lead efforts in prospective data collection study from a small group of Swiss patients in longitudinal studies in collaboration with the clinical experts from the Breast Cancer Center of the University of Geneva Hospitals (HUG). The methods employed in that study are mixed, including face to face entry/intermediate/exit interviews, surveys, and focus groups, as well as passive wearable (Withings Scan Watch 2)/smartphone data collection and modeling methods (via the mQoL Living Lab).

Via user-centric design methods and interactive additive data acquisition and modeling approach, aspects of data quality, methods’ feasibility, reliability, and validity shall be scrutinized. The candidate is also expected to lead efforts in acquisition and management of selected retrospective datasets (EHR by HUG), which, however, will include only rudimentary behavioral and life quality outcomes.

The research conducted within this candidate will contribute to software being continually developed by the QoL Lab members and constituting the mQoL Living Lab (implying Android/iOS, Flutter, Python, Kotlin). The applicant should be comfortable using standard machine learning libraries (e.g., sk-learn, pandas, PyTorch, and TensorFlow/Keras) and data visualization 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 project.

The principal QoL supervisor is Professor Katarzyna Wac, while the daily co-supervisor is MSc Alexandre Horst. The clinical co-supervisors are Dre Anita Wolfer and other clinicians from the HUG’s Breast Cancer center.

Main Responsibilities Include:

  • Holding a role of a teaching assistant for the selected UNIGE courses taught by Prof. Wac.
  • Holding a role of a research assistant: Managing own research within the QoL Lab scope and the scope of the EMBED project (including project code, datasets, project deliverables, papers, other proposals, etc., depending on the level of seniority); note that this research project implies completely managing own real-life settings study titled VitaQoL with recruited patients in Geneva area (N: at least 30, length: at least 24 months). 
  • Contributing additional mQoL Living Lab features, including integrating new wearables’ APIs and new machine learning methods (including deep learning) for data analysis and predictive/prescriptive models of behavioral, health, and life quality outcomes.
  • Executing full lifecycle mQoL Living Lab software development and evaluation in real-life settings with a set of patients in the scope of the EMBED project.
  • The position requires living in (or relocating to) Geneva and being present in the office and/or the clinic.
  • Note: Clinical knowledge of the domain is NOT required, but it is welcome.
  • Please feel free to apply even if you think your expertise and interest only partially fulfill these responsibilities.

The chosen candidate will be hired on a 1-year renewable contract. The position has a maximum duration span of 5 years. In the first year, there is a 3-month trial period during which both parties can terminate the working agreement.

Formal Requirements
Applicants should hold a MSc degree in computer science, bioinformatics, human-computer interaction, or related fields with excellent results and professional English and French. As criteria for assessing the qualifications, emphasis will also be laid on previous projects, publications, and relevant clinical, human subjects studies or industrial experience (if any).

At this time, only applications from EU/Swiss candidates can be considered. Application deadline: 2 July 2026 EOD.

Application Procedure

The application, in English, must be submitted electronically as one PDF file to Prof. Katarzyna Wac (katarzyna.wac@unige.ch) and MSc Alexandre Horst (alexandre.horst@unige.ch). Please include:

  • Motivation letter including a summary of the planned research project in the first year and its match with the required responsibilities (1 page)
  • Detailed, up-to-date CV and publication list, including Google Scholar profile link and, if applicable, grant acquisition experience 
  • Diplomas and transcripts of records (BSc, MSc)
  • Other information for consideration, e.g., portfolio, GitHub repository links
  • Full contact details (name, full affiliation, and email) of 3 relevant referees

The University of Geneva is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability, or age.

Questions

For specific information about the position, please contact Prof. Katarzyna Wac (katarzyna.wac@unige.ch) and MSc Alexandre Horst (alexandre.horst@unige.ch).

If you wish to meet us before you apply feel free to join our QoL Summer School starting on 29 June 2026 – see details on the WEB.