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The University of Witten/Herdecke (UW/H) is the first privately funded university in Germany. Founded in 1982, it has since established itself as a significant educational institution in Germany. Currently, a total of 3,000 students are enrolled in the faculties of Health and Management, Economics and Society in Witten.

We are seeking to strengthen the team of the Professorship for Quantitative Methods (Prof. Dr. Lukas Stoetzer) at the Faculty of Management, Economics and Society.

A position (full-time) as

Post-doc (m/f/d)

in the project 'Election Forecasts for the German Federal Election 2025' is to be filled as soon as possible.

The position is initially limited to three years, with the aim of long-term cooperation.

The Project

The Post-doc will work in the project funded by the German Research Foundation, 'Election Forecasts for the German Federal Election 2025'. Collaboration partners include, among others, the University of Mannheim and the Hertie School, Berlin. The project's goal is to forecast the 2025 German federal elections. It focuses on developing dynamic forecasting models, collecting and analysing primary and secondary data, and examining the impact of election forecasts on political behavior and attitudes. The project module based at the University of Witten/Herdecke deals with the development and improvement of forecasting models for the German federal elections. The aim is to provide predictions for various election outcomes, focusing on the methodological extension of existing models, the integration of constituency data, and the incorporation of coalition formation forecasts.

Your Responsibilities

  • Research and Model Development: Develop and apply advanced statistical models and machine learning algorithms to enhance the accuracy of election forecasts.
  • Data Management and Analysis: Contribute to the establishment and maintenance of a comprehensive database for election forecasts.
  • Communication and Publication: Write scientific articles, give presentations at conferences, and contribute to the public communication of the project.
  • Collaboration with Project Partners: Work closely with other project partners to integrate research approaches and create synergies.

Your Profile

  • A completed doctorate in political science, statistics, economics, or a related field.
  • Expertise in statistical modelling, machine learning, and data analysis.
  • Experience in handling large datasets and proficiency in programming languages R or Python.
  • A thorough understanding of political processes, ideally with a focus on German federal elections.
  • Excellent communication skills and experience in collaborating within research teams.

We Offer

  • Work-life balance (flexible working hours)
  • Option for remote work
  • 30 days of annual leave and additional free bridge days; the 24th to 31st December and three bridge days are additionally non-working days
  • Reimbursement of childcare costs up to €200 per month (dependent on salary level and age of the child)
  • Company pension scheme and disability insurance
  • An extensive training program
  • Promotion of eco-friendly mobility (bicycle leasing, rental of electric cars, etc.)
  • A discounted job ticket for public transport
  • A wide range of culinary options in our cafeteria at employee prices
  • Various sports offers for employees

Application

If interested, please send us your application documents by 05.04.2024 with the usual proofs exclusively electronically via our application form on our website. Questions and further information can be addressed via the email address below. We look forward to your application!

Contact

Prof. Dr. Lukas Stoetzer

Email: lukas.stoetzer@uni-wh.de

Faculty of Economics and Society
University of Witten/Herdecke
Alfred-Herrhausen-Straße 45
D – 58455 Witten

Vielfaltsgedanke

Die Universität Witten/Herdecke lebt den Vielfaltsgedanken ausdrücklich (www.uni-wh.de/diversity). Sie verfolgt das Ziel, die Vielfalt ihrer Mitglieder zu fördern und berücksichtigt die Kompetenzen und Besonderheiten, die diese z.B. aufgrund ihres Alters oder ihrer körperlichen Konstitution mitbringen. Eine Erhöhung des Frauenanteils am wissenschaftlichen Personal wird proaktiv angestrebt.