WA 29/22

Are you looking for a new professional challenge? Then this is the place to be! Become part of our international team! 


The Zuse Institute Berlin (ZIB) is a non-university research institute under public law of the State of Berlin. We conduct research and development in applied mathematics and computer science as well as the analysis and processing of complex data in conjunction with high-performance computing. 

For the Computational Humanities research group, which is part of the department Modeling and Simulation of Complex Processes, we offer a fixed-term contract at the next possible date for a period of two years, with the option of extension, for a 

Scientific Employee (f/m/d)
Reference Code WA 29/22
Pay Grade 100 % - E13 TV-L Berlin. 

The Project 

For the BMBF funded project MODUS-COVID, we are seeking a new member for our research team to develop and implement methods for modelling and simulating infection dynamics and for analyzing the relevant data. 

The goal of the MODUS-COVID project is to investigate the effects of non-pharmaceutical interventions (NPIs) on the infection dynamics of SARS-CoV-2. The project also aims to improve the understanding of infection chains and the dynamics of spread within urban areas as well as in a regional and nationwide context. The project is conducted in collaboration with TU Berlin (Prof. Kai Nagel). 

Working towards a PhD within this project is possible. 

Your Tasks 

  • contribution to the project and close cooperation with other project partners, 
  • analysis and integration of several data sources to adapt the modelling to actual observed data, 
  • development of new methods for modelling and simulation of infection dynamics, 
  • implementation of the algorithms, 
  • visualization and validation of the results. 

Your Profile 

  • an above average Master’s degree in Mathematics (or related fields), 
  • significant experience in mathematical modelling in the area of spreading dynamics, programming skills in C/C++, Java or Python and hands-on experience in real-world data analysis; experience in Agent-based modelling and machine learning is a plus, 
  • excellent communications skills (writing, speaking) and working proficiency in English, 
  • strong team player with affinity for research and a focus to see things working in practice; methodical and conceptual strength and creativity. 

We offer a family-friendly working environment through flexible working and meeting times, excellent equipment and a challenging professional environment. 

Additionally, we offer 

  • comprehensive training in a competent and cooperative team, 
  • an additional pension scheme (VBL), 
  • 30 days annual leave, flexible working hours (flexitime), 
  • a salary in accordance with TV-L (Collective Agreement for the Public Service of the Federal States), taking into account the relevant professional experience, 
  • an end-of-year bonus, 
  • discounted BVG (public transport) ticket as part of the capital city allowance, 
  • and the use of canteens and sports programs of the Freie Universität Berlin at reduced rates. 

Female applicants are highly encouraged to apply. Since women are underrepresented in information technology, the ZIB is trying to increase the proportion of women in this research area. 

Disabled persons are given preference in the event of equal suitability. 

Please send your application, quoting the reference code WA 29/22, including a cover letter containing a statement of your research interests, your CV and the standard supporting documents, by 15 August 2022 (date of receipt) as one PDF file to jobszib.de 

Our private policy statement regarding application data is available at www.zib.de/impressum

For further information on the area of responsibility, please contact Dr. Nataša Conrad (natasa.conradzib.de). 

For further job offers please visit our website at www.zib.de/jobads

Student Assistant (f/m/d) Visual and Data-Centric Computing
Student Assistant - 3D Human Spine Modeling and Articulation (f/m/d)
Wissenschaftlichen Angestellten (w/m/d) in der Abteilung Distributed Algorithms
Studentische Hilfskräfte (w/m/d)