DIS PhD Graduate Program | 2025

Temporary, Part-time · Vienna

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WE SEARCH FOR
We are looking for students who want to use their exceptional knowledge and skills to make a meaningful difference in society – whether supporting the green transition, combating crime and misinformation, improving healthcare outcomes, or building more equitable economies. Applicants should be interested in having a substantial degree of independence in their work and be curious about a breadth of topics within the research areas of the Complexity Science Hub. They should be open communicators, and enjoy collaboration and sharing their expertise and ideas with others. 

Read about the Graduate Program in Complexity Science here
YOUR PROFILE
  • Masters/diploma degree in the natural, physical, or social sciences, mathematics, computer science, engineering, or related disciplines with a strong quantitative foundation; or another degree but with at least two years of full-time research experience in a quantitative area. 
  • Prior independent research experience so as to be familiar with the research process
  • Comfort with a programming language such as Python, R, Mathematica, Matlab, or Julia, or a database management and query language such as SQL; and/or substantial experience with statistical packages such as SPSS, SAS, or Stata
  • Proficiency in English
WE OFFER
The Graduate Program in Complexity Science has a limited number of fully funded opportunities for exceptional students to do their doctoral studies at the Complexity Science Hub and one of its partner universities. The program consists of: 
  • independent  thesis research, determined by each student’s interests
  • two ~3-month research exchanges: one in government, public administration, or EU institution; and one in industry or business
  • coursework and workshops, including an annual series of Complexity Science Hub “master classes” led by prominent guest lecturers
  • participation in the Complexity Science Hub research talk series, with regular presentations
  • organization of and participation in an annual graduate student symposium
APPLICATION
  • The application deadline for the current call is 01 December 2024 (24:00 Vienna local time). Admitted students will begin their PhD in September-October 2025.
  •  Application materials should be submitted through our online portal. Letters of recommendation must be sent directly to applications@csh.ac.at.
  • A complete application includes:
    • curriculum vitae (CV)
    • vision letter / cover letter – What problems/challenges would you like to solve? Why is the Complexity Science Hub the right place for you?
    • supplementary application form
    • list of inventions
    • two letters of recommendation (sent directly by the recommender)
      Subject: DIS PHD - FirstName LastName (of the applicant)
Late or incomplete applications cannot be reviewed.

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About us
The Complexity Science Hub (CSH) is Europe’s research center for the study of complex systems. We derive meaning from data from a range of disciplines – economics, medicine, ecology, and the social sciences – as a basis for actionable solutions for a better world. Established in 2015, we have grown to over 70 researchers, driven by the increasing demand to gain a genuine understanding of the networks that underlie society, from healthcare to supply chains. Through our complexity science approaches linking physics, mathematics, and computational modeling with data and network science, we develop the capacity to address today’s and tomorrow’s challenges.
Über uns
Das Complexity Science Hub (CSH) ist Europas Forschungszentrum für die Untersuchung komplexer Systeme. Wir leiten Bedeutung aus Daten verschiedener Disziplinen ab - Wirtschaft, Medizin, Ökologie und den Sozialwissenschaften - als Grundlage für handlungsorientierte Lösungen für eine bessere Welt. Seit unserer Gründung im Jahr 2015 sind wir auf über 70 Forscher angewachsen, angetrieben von der zunehmenden Nachfrage nach einem echten Verständnis der Netzwerke, die der Gesellschaft zugrunde liegen, von der Gesundheitsversorgung bis hin zu Lieferketten. Durch unsere komplexen wissenschaftlichen Ansätze, die Physik, Mathematik und computergestützte Modellierung mit Daten- und Netzwerk-Wissenschaften verknüpfen, entwickeln wir die Fähigkeit, die Herausforderungen von heute und morgen anzugehen.   
   
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