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PhD student position in Implementation Science in Health Care (UMZH Learn4Sepsis) 80 %

Universität Zürich Zürich 07.11.2026 Déposer ma candidature
Entreprise
Universität Zürich
Lieu
Zürich
Date
07.11.2026
Référence
382012

Advance Your Research Career in a Leading Academic Environment

Join one of Switzerland's largest universities, home to approximately 10,000 employees and a hub for cutting-edge research and top-class education. With 12 professional apprenticeship streams and a diverse range of subject areas, the institution provides an inspiring working environment where talent and skills are put to work effectively.

Key Responsibilities

  • Complete scientific qualifications for a PhD while contributing to the UMZH Learn4Sepsis project.
  • Manage diverse project activities, including coordinating project interest holders and contributing to workshop activities.
  • Develop human-centered design frameworks for innovations developed within the Learn4Sepsis consortium.
  • Collect and analyze both qualitative data (such as observations and semi-structured interviews) and quantitative data (such as questionnaires).
  • Disseminate research results through presentations at conferences and publications in peer-reviewed journals.
  • Supervise and support undergraduate students.
  • Conduct literature reviews and synthesize scientific content.

Required Profile

  • Master's degree or equivalent in implementation science, health services research, organizational sciences, public health, psychology, sociology, health economics, behavioral science, or a related field. MD-PhD candidates will be positively considered.
  • Strong interest in keeping up with emerging trends and best practices in the respective research fields.
  • Strong planning and organizational skills, excellent oral and written communication, and effective interprofessional skills.
  • Fluency in English and German; French is an advantage.
  • Self-motivated with a comfort level in taking initiative.
  • Sound knowledge of empirical methods and advanced statistics.
  • Excellent computer application knowledge, specifically in MS Office, SPSS, and R.
  • Experience with qualitative data management software, such as MAXQDA, is an advantage.

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