The Algorithms & Complexity group at TU Wien invites applications for a PhD position in computer science in the area of QBF solving.

Job Description

The PhD student will work with Friedrich Slivovsky and Stefan Szeider on the project Learning to Solve Quantified Boolean Formulas funded by the Vienna Science Fund (WWTF), which aims to provide a new perspective on QBF solvers in terms of strategy learning algorithms. As part of this project, the successful candidate will

1) develop new QBF solvers based on learning, and 2) analyze the complexity QBF solving using concepts and ideas from computational learning theory.

This is a three-year full-time position that comes with a competitive salary (approx. EUR 52,000.00 gross, p.a.). The expected starting date is October 2020, but due to current circumstances, this is open to negotiation.


Applicants need to have or be close to obtaining a MSc degree or a 4-year BSc degree in computer science or mathematics.

The successful candidate is expected to have a strong background in computational logic and solid programming skills (preferably in C/C++). Knowledge of standard machine learning models is an advantage, as are prior publications in an area related to the scope of the project (such as propositional satisfiability).

Applicants must be strongly motivated for doctoral studies; should possess the ability to work independently and perform critical analysis, and also have good levels of cooperative and communicative abilities. They also need to have a very good command of English in writing and speaking to be able to participate in international collaborations and to publish and present research results in international conferences and journals.


The application deadline is July 20th, 2020 at midnight local time. Early applications are welcome to speed up the recruitment process but all applications submitted before the deadline will be considered.

Applications must be sent to and should include the following documents (in a single PDF file):

  1. Curriculum vitae.
  2. University grade transcripts.
  3. A motivation letter that includes a description of the applicant's qualifications and interests.
  4. Diploma and transcripts of records (BSc and MSc).
  5. If applicable, copies of the applicant's MSc thesis (or possibly BSc thesis) and any research publications.
  6. Names and addresses for two references who might be contacted for reference letters later in the recruitment process.

Please observe that all the documents above should be in English (for official documents German is fine as well).

Further Information and Contact Details

For further inquiries about this position, please contact Friedrich Slivovsky at