Doctoral Researcher in Survey Methodology

14 May 2024
Job Information

Organisation/Company

GESIS - Leibniz Institut für Sozialwissenschaften

Department

Cologne/Mannheim

Research Field

Sociology

Researcher Profile

First Stage Researcher (R1)

Country

Germany

Application Deadline

4 Jun 2024 - 23:59 (Europe/Berlin)

Type of Contract

Temporary

Job Status

Part-time

Offer Starting Date

1 Oct 2024

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Reference Number

SDM-165

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

GESIS – Leibniz-Institute for the Social Sciences is an internationally active research institute, funded by federal and state governments and member of the Leibniz Association.

Starting on 1. October our Department Survey Design & Methodology (SDM), Team Survey Statistics located in Mannheim, is looking for a

Doctoral Researcher in Survey Methodology

(Salary group 13 TV-L, working time 75% for the duration of 3 years)

 

The department Survey Design & Methodology (SDM)  is both nationally and internationally recognized for its expertise in survey methodology, gained over many years by conducting own research as well as consulting on and implementing renowned survey projects.

The externally funded project "Explaining nonresponse and countering nonresponse bias in self-administered panel surveys" (ENCONOBS) is an interdisciplinary research project to explain and mitigate nonresponse bias in self-administered panel surveys with a strong focus on the application and further development of causal machine learning methods. The project is carried out in cooperation with the Universities of Düsseldorf and Hamburg.

 

Your tasks will be:

• Analysis of nonresponse bias in various self-administered panel surveys
• Implementation and analysis of experiments to increase participation in panel surveys
• Close cooperation with all project members at the participating institutions
• Conducting own research as part of a doctorate

Your profile:

• Scientific university degree in social sciences, economics or a related field, preferably with a focus on statistical analysis
• Experience in analyzing complex survey data (e.g. international or panel surveys) is an advantage
• Experience in the areas of causal inference and machine learning is an advantage
• Knowledge of the statistical software R, further programming skills (especially in Python) are an advantage
• Proficient in written and spoken English and German

Our Benefits:

• Collaboration in an interdisciplinary research project funded by the German Research Foundation (DFG)
• Development of quality standards for future data collection
• Flexible working hours and the possibility of up to 60% mobile working within Germany
• Very good conditions for reconciling work and family life, e.g. subsidies for childcare for children who have not yet attained the age of compulsory schooling resp. child care slot with Fröbel Erziehung und Bildung gGmbH
• Holistic company health management and discounted participation in the university's sports programme
• Generous support for your pension provision as a direct insurance policy
• Promotion of your skills through further training measures

For further information concerning the tasks please contact Dr. Barbara Felderer via phone +49 621-1246-189 or via E-Mail .  If you have questions about the application process, please contact Helena Rustler via E-Mail .

Interested?

Please apply via our Online-application portal until 04.06.2024.

Our reference number is: SDM-165

Requirements

Research Field

Sociology

Education Level

Master Degree or equivalent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

GESIS - Leibniz-Institut für Sozialwissenschaften

Country

Germany

City

Mannheim

Postal Code

68159

Street

B6, 4-5

Geofield

Where to apply

Website

https://www.hidden-professionals.de/HPv3.Jobs/gesis/stellenangebot/37729/Doctor…

Contact

City

Cologne

Website

http://www.gesis.org/home/

Street

B6, 4-5

Postal Code

68159

E-Mail

[email protected]

STATUS: EXPIRED