Institute for Education
Postdoctoral Researcher in Modeling Intraindividual
Learning Trajectories with Intensive Longitudinal Data
The Institute of Education at the University of Zurich is accepting applications for a Postdoctoral Re-
searcher for modeling intensive longitudinal educational testing data. The work load is negotiable and
the initial appointment will be until February 29, 2024. The position primarily involves work in the
methodological research project “Modeling Developmental Trajectories with Intensive Longitudinal
Data from Large-Scale Formative Assessments” funded by the Swiss National Science Foundation (PI:
Prof. Dr. Martin Tomasik). It is a full research position with no teaching obligations, but teaching con-
tracts can be negotiated to temporarily or permanently complement a part-time employment in the
project.
Your Responsibilities
The successful candidate will collaborate in a team comprising another post-doctoral researcher and a
PhD student. Against the backdrop of intensive longitudinal data from a computer-based tool for form-
ative student assessment (see Tomasik, Berger & Moser, 2019, in Frontiers of Education), the successful
candidate will apply and develop methods for modelling intraindividual learning trajectories and as-
sessment characteristics across different subject domains, investigate patterns of heterogeneity in these
trajectories, study the longitudinal dynamics between concepts and content domains, and investigate
contextual factors predicting learning trajectories. A significant portion of the working time will be de-
voted to prepare the results of this modelling for publication in scientific journals and presentation at
international conferences. The successful candidate might also be involved in mentoring a doctoral
student.
Your Qualification Requirements
Qualified candidates should be self-driven and highly motivated individuals with an established track
record, including first-author publications in top-tier international journals. They should have a good
statistical and/or computational background in order to apply and contribute to development of meth-
ods such as item response theory, time-series analysis, dynamic systems, growth curve modelling and/or
other related methods capable of separating between-person and within-person variance, in order to
study interindividual differences in intraindividual change. A solid knowledge of item response theory,
good command of machine learning approaches, and programming skills (e.g., R, Python, C/C++,
MATLAB) are a strong advantage. The successful candidate should have obtained a doctoral degree in
psychology, mathematics, statistics, computer science, psychometrics, developmental measurement or
educational measurement no longer than seven years ago and bring along some experience – or at
least strong interest – in developmental and/or educational research. A good command of English
and/or German (as the working languages in the project) is mandatory, familiarity with any of the other
national languages (i.e., French and Italian) could be helpful.
Our Offer
We offer great working conditions on a unique data set (N ≈ 100.000) and the opportunity to signifi-
cantly expand one’s publication record. This interdisciplinary research project is conducted in collabo-
ration with leaders in the field of machine learning, signal processing theory, computational social sci-
ence, and data analytics. The University of Zurich provides great opportunities for networking within
and beyond the Digital Society Initiative (see https://www.dsi.uzh.ch/). The Institute offers an attrac-
tive salary plus a very generous social benefits package, five weeks of paid vacation per year, flexible
working hours as well as a highly motivated and supportive team of scientific and non-scientific per-
sonnel.
Application Procedure
To apply for this position, please submit in one single PDF file (1) a cover letter describing your past
training and your future research goals, highlighting why your background and interests are a good
match for the position, (2) a one-page curriculum vitae, (3) a full list of publications, (4) a copy of the
doctoral certificate, and (5) three writing samples (i.e., papers published or accepted for publication) to
Prof. Dr. Martin Tomasik (martin.tomasik@ife.uzh.ch). Letters of reference (if available) may be sent
directly to Prof. Dr. Martin Tomasik. Review of applications will begin immediately and continue until
the position is filled. Interested applicants are strongly encouraged to submit their applications at their
earliest convenience. Preferred starting date is as soon as possible. Confidential inquiries concerning
this vacancy may either be directed to Prof. Dr. Martin Tomasik or Dr. Charles Driver
About Us
The research project is situated at the Chair of Methods for Developmental and Educational Research
within the Institute of Education (IFE) at University of Zurich. The IFE is the largest educational science
institute in Switzerland and conducts basic and applied research on central scientific and social issues
in formal, non-formal, and informal educational contexts such as school, family, the work environment,
or youth work (see https://www.ife.uzh.ch/en.html). The Institute for Educational Evaluation (IBE)
is a close collaboration partner, and is mainly engaged in the field of standardized performance meas-
urement. It carries out school effectiveness studies as well as educational surveys and longitudinal stud-
ies relevant to education. The IBE also develops software for large-scale adaptive testing and formative
assessment (see https://www.mindsteps.ch/) which is implemented in several cantons of Switzerland
and also used for research purposes. Located close to downtown Zurich and only seven minutes from
the main station, the Institute is perfectly accessible by public transportation. The city of Zurich itself
has consecutively been awarded “city with the world's best quality of life” seven times on Mercer re-
search. With its culture, nature and urban-style living, it offers numerous opportunities for leisure and
social life.