Here is a position advertised at Bielefeld University. If you are
interested and want more information you can contact me at odile.sauzet@uni-
bielefeld.de
The official advert for this position is here https://www.uni-bielefeld.de/(
de)/Universitaet/Aktuelles/Stellenausschreibungen/Anzeigen/Wiss/wiss19199.
pdf in German only. But I strongly welcome application in English from
non-German speakers.
What it says is the following
The Department of Epidemiology and International Public Health of the
Bielefeld School of Public Health (head: Prof. Dr. Oliver Razum) seeks a
highly motivated individual to work in the PhD Project “DEPRIV”
(Identifying, conceptualising, and modelling micro-area factors with
effects on the health of vulnerable populations). This project is part of
the German Science Foundation funded Research Unit PH-LENS (Refugee
migration to Germany: a magnifying glass for broader public health
challenges) which offers an interdisciplinary work environment with
collaborators in institutions based in Bielefeld, Berlin, Dresden and
Munich. An aim of DEPRIV is to investigate methodological/statistical
issues to be resolved to include increasingly smaller spatial levels in
indexes of multiple deprivation comprising multiple
political/spatial/institutional scales.
The specific tasks are:
work in DEPRIV Project: develop and validate new statistical
methods for the construction of indexes of multiple deprivation under the
supervision of the project PI Dr. Odile Sauzet. Collaborate with other
project members in particular with Dr. Werner Maier at the Helmholtz Zentrum
in Munich and Research Unit members. Participate in the young researcher
workshops of the research unit PH-LENS (95 %)
contribution to the general organisation of the department’s work as
well as active participation in academic self-government (5 %)
Your Profile
We expect
university degree (master) in a relevant field (mathematics,
statistics, human geography with a strong statistics component)
interest in working in an interdisciplinary team
interest in social epidemiology
knowledge of R programming
very good communication skills in English (oral and written)
Preferable qualifications
knowledge of statistical methods for spatial data
experience in applied statistics (preferably with spatial data)
experience in applying methods for the construction of indexes of
multiple deprivation (shrinkage estimation)
You may leave the list at any time by sending the command
SIGNOFF allstat
to [log in to unmask], leaving the subject line blank.
|