Call for Doctoral Students in Social Network Analysis, Algorithms and Fair Machine Learning

We are looking for highly qualified and motivated individuals to pursue a Ph.D. in the areas of social network analysis, (theory of) algorithms and fair machine learning. The prospective Ph.D. students will join a research team at TU Wien led by assistant professor Stefan Neumann.

Research directions:

Several research directions for the Ph.D. project are possible and the concrete topic will be determined in collaboration with the Ph.D. candidate. The research can either be more theoretical or more applied, based on the candidate’s profile and interests. The following three areas may be particularly appealing based on our group’s profile:

  • Social network analysis, e.g., mitigating polarization and disagreement in networks.
  • Development of practical data science algorithms with provable guarantees, e.g., by leveraging theoretical insights to obtain state-of-the-art practical algorithms.
  • Algorithms for fair and transparent machine learning, e.g., concerning the real-world impact of machine learning models.

Your profile:

  • Successful applicants should have an outstanding academic track record, as well as a strong background in at least one of the following areas: algorithm design, mathematics (especially probability and optimization), machine learning, social network analysis and/or computational social science.
  • We are looking for doctoral students who are highly ambitious and whose goal is to publish papers at internationally leading computer science conferences.
  • English language skills (level C1 or C2). German skills are a benefit but not required.

What we offer:

  • Competitive salary funded for four years.
  • Low teaching load.
  • The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world.
  • A workplace in the city centre of Vienna, one of the most livable cities in the world.
  • Hybrid working style with a home office option.
  • A range of attractive social benefits (see Fringe-Benefit Catalogue of TU Wien).

Admission requirements: The successful candidate must have passed a second cycle degree (for example a master’s degree) in a relevant field before starting the position.

Applications must include the following elements in a single PDF:

  • Application letter with a brief description of why you want to pursue research studies, about what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long).
  • CV including your relevant professional experience and knowledge.
  • Copies of diplomas and grades from previous university studies and (if available) certificates of fulfilled language requirements.
  • Representative publications or technical reports: For longer documents, please provide a summary (abstract) and a web link to the full text.
  • Two reference letters from professors (or other collaborators) which should be sent by the referees directly to Stefan Neumann.

Application deadline: To receive full consideration, the documents must be submitted in a single PDF by mail to Stefan Neumann on or before February 21. After that, applications are still possible but may not be considered anymore. Recommendation letters must be received by March 7.

First day of employment: A starting date in the middle of 2025 is desired, but earlier or later starts are possible.

We are committed to increasing the gender diversity of our group. Female and non-binary applicants are explicitly encouraged to apply. Preference will be given to minority groups when equally qualified.

If you have any questions regarding this position, do not hesitate to contact me by mail.