The Institute of Social and Preventive Medicine (ISPM) of Bern performs research in a range of disciplines relevant to public health ( ?url=www.ispm.unibe.ch&module=jobs&id=204876" target="_blank" rel="nofollow">?url=www.ispm.unibe.ch&module=jobs&id=204876" target="_blank" rel="nofollow">www.ispm.unibe.ch ). Groups cut across divisions, facilitating an interdisciplinary approach to research in the fields of clinical epidemiology, social and behavioral health, biostatistics, and international and environmental health.
We are seeking a highly motivated PhD student to be involved in a research project entitled: “The Risks and Benefits of Integrating Emotions in End of Life Communication” funded by the Swiss National Science Foundation. Through different research studies, the overarching aim of the project is to explore the role of emotions in medical practice. The main focus is to understand how physician emotions are present in their interactions with patients, how are they managed, what is their impact on patient care and on physician’s wellbeing, as well as what are the expectations of families and patients.
Period: Fixed-term contract for up to 4 years, starting February 2022 (negotiable).
Salary: Swiss National Science Foundation PhD salary rate (47,000 to 50,000 CHF, 100%).
Place: ISPM, University of Bern, Switzerland
Application deadline: Review of applications will start mid-December 2021 and continue until the position is filled.
Prepare study materials for ethical review and data collection with support from the supervisor
Support participant recruitment activities, collect and analyze data, drawing relevant conclusions with support from the supervisor(s)
Be responsible for the progress and quality of his/her own research work and report progress regularly to the supervisor(s)
Provide ready access to all data for the team and/ or supervisor
Prepare, maintain, and update website materials with scientific information
Draft publications and abstracts and present the results at (inter)nationally recognized conferences and workshops
Prepare other articles, reports, and presentations for dissemination of results
Work systematically to complete the doctoral degree in no longer than four years
Ability to work efficiently, independently, and with interdisciplinary teams
Excellent communication and organizational skills
Prior knowledge of and experience with:
o Descriptive and inferential statistical techniques and /or
o qualitative methods (experience with grounded theory and/or thematic analysis is desirable)
The possibility is open for the candidate to work exclusively with qualitative methods, quantitative methods, or with mixed methods. Please indicate a preference in the motivation letter, highlighting relevant experience
Excellent knowledge of English and German, written and spoken. Knowledge of Swiss German or any other of the Swiss national languages is desired but not mandatory
Well equipped to work with data collection software (e.g. qualtrics, unipark) and data analysis software (e.g. NVivo, R, etc.)
Applicants are welcome from a range of disciplines, including but not limited to: psychology, medicine, anthropology, sociology, or health services research
An international, multidisciplinary, and highly stimulating academic environment
Support for career development and mentoring
Funds for project related training, travel, and conference attendance
PhD Salary according to the pay rates of the Swiss National Science Foundation
Contact and Address
For further information on the position, please contact Prof. Sofia C. Zambrano Tel. +41 31 684 57 76 ( sofia.zambranoispm.unibe.ch ).
Please send your application in one PDF-file to hrispm.unibe.ch with copy to sofia.zambranoispm.unibe.ch
Applications must be submitted in English and include:
a letter of motivation outlining your interest in the area and how your background relates to the research topic
a CV with contact details of 2 academics who can be contacted immediately if shortlisted
a sample of scientific writing either in the form of a scientific publication or a file of the master thesis