University or Organization: University of Fribourg
Department: Autism, Bilingualism, Cognitive and Communicative Development, Faculty of Science & Medicine
Job Location: Fribourg, Switzerland
Web Address: https://www.unifr.ch/med/de/research/group/durrleman/
Job Title: Post-Doctoral Researcher in Data Analysis
Job Rank: Post Doc

Specialty Areas: Cognitive Science

Required Language(s): English (eng)

Description:

The Autism, Bilingualism, Cognitive and Communicative Development (ABCCD) group in Fribourg, Switzerland is looking for a post-doctoral senior expert in data analysis to join their team (starting between April/May and September 2024), either full time/90% for 18 months (75,000 chf per year) or part time/60% for 2.5 years, with a slight preference for the latter arrangement.

This member of our team will bring expertise in statistics and will be instrumental in the discussion and support of ongoing data analyses, training/ advice in the use of specific analysis techniques and interpretation of the results along with the team members. The candidate will also be comfortable in academic writing in English as s/he will play an integral role in preparing/co-authoring manuscripts for publication, thus a solid track-record attesting to academic writing skills is required.

Our collaborator will ideally come from the field of experimental psychology to facilitate gaining a full grasp of our research questions on bilingualism and autism, and methods applied to address them. Most studies underway in our group are concerned with elucidating the impact of bilingualism on cognition and communication and determining which potential mediators play a role. We are seeking someone to help us decide on the most suitable statistical techniques to analyze these very complex relationships, capable of incorporating both cross-sectional and longitudinal data to evaluate the relevance of bilingualism as a predictor of our dependent variables, integrating both continuous and categorical predictors at all levels of measurement (i.e., subject- and time-varying), and handling missing data (e.g., due to some children not completing all tasks in the protocol, dropout, etc). Ideally, s/he would be comfortable with an array of techniques (linear mixed effect regression, Bayesian Analysis, Structural Equation Modeling, cluster analyses, Latent Class Analysis, Deviation Sum Coding…).

Interested candidates should send a CV (including 2 potential references) and letter of motivation to the contact's email listed below.

Application Deadline: 15-Jan-2024
Mailing Address for Applications:

Email Address for Applications: [email protected]
Contact Information:
Prof. Dr. Stephanie Durrleman
Email: [email protected]