项目介绍

2026年11月12日

UniBE is ambitious.
With us, you deliver top performance and test your skills against the best.

• Conducting cognitive task analyses with members of the science ‘sleuth’ community.
• Co-organising and running workshops with sleuths.
• Analysing these qualitative data to develop a taxonomy of sleuthing practices.
• Creating a roadmap for such checks that can be formalised into methods and tools.
• Teaching opportunities are available in English and/or German, but there are no teaching requirements.

Your profile

Essential:

• A PhD in Psychology, Human-Computer Interaction, Epidemiology, Research Methods, or a related field.
• Demonstrated interest in (forensic) meta-science, scientific error detection, trustworthiness assessment, or quality assessment within research synthesis.
• Comfortable working closely with people, building rapport with expert practitioners and eliciting knowledge from them.
• Strong written and spoken English.
• Willingness to commute or relocate to Bern, Switzerland, and begin by between February 1st and April 1st. This is an in-person or hybrid commuting position; remote work is not available.

Desirable:

• Familiarity with cognitive task analysis, process tracing, think-aloud protocols, or similar methods for eliciting how experts work and why.
• Experience designing, conducting, and analysing qualitative research (e.g., in-depth interviews, observation, thematic or framework analysis).
• Familiarity or prior experience with science sleuthing (e.g., PubPeer, forensic meta-science checks).

• Salary in accordance with University of Bern regulations.
• English-speaking research group.

We explicitly encourage applications from women and candidates from underrepresented backgrounds in academia.

Applications will be considered on a rolling basis until filled. Apply by November 30, 2026 for full consideration.

Send the following documents to ian.hussey@unibe.ch:

• Motivation letter (max 2 pages) describing relevant skills and research interests.
• Academic CV, including publications and preprints; relevant technical skills and evidence of them (i.e., links to your GitHub and OSF profile or similar).
• Contact information of 2 references.
• A one-page document describing between one and two representative projects that demonstrate your interests and skills relative to the project. This can be broadly conceived. For example, these could include a brief description of the relevance of a publication or preprint, a qualitative or interview study you conducted, a PubPeer comment you have written, an R package or method you have contributed to, or your involvement in a meta-science initiative.