Open positions in the Cluster of Excellence “Bilateral AI” at Graz University of Technology

Open research positions: 2 PhD positions

We are seeking highly motivated and talented individuals to join our dynamic research team for combining symbolic and sub-symbolic AI. The successful candidates will conduct research at the Graz University of Technology in collaboration with our partner institutes JKU, AAU Klagenfurt, ISTA, TU Graz, TU Vienna, and WU Vienna. 

Job description:
The vision of Bilateral AI, is to educate a new generation of top-quality AI scientists with a holistic view on symbolic and sub-symbolic AI methods. The training will be distributed over the six participating Universities. Joint seminars, scientific workshops, and compulsory courses outside the PhD students’ research fields, will be also be designed to encourage interdisciplinarity. Each student will be supervised by two experienced and internationally renowned professors with different research fields (symbolic / sub-symbolic AI). The training will also provide a career development program, advice and support for students with innovative business ideas, and workshops for presentation and soft skills.

Requirements:
   
• MSc degree in AI, Computer Science, Mathematics, Statistics or related fields 
    • background on Machine Learning or Automated Reasoning
    • experience with programming in Python or C/C++
    • strong written and verbal communication skills
    • willingness and ability to work in a team

What we Offer:
   
• PhD: On the basis of full-time employment (40 hours/week) 
    • Opportunity to work together with leading experts in the field
        ◦ Prof. Robert Legenstein
        ◦ Prof. Elisabeth Lex
        ◦ Prof. Wolfgang Maass
        ◦ Prof. Ozan Özdenizci
        ◦ Prof. Robert Peharz
        ◦ Prof. Thomas Pock
        ◦ Prof. Franz Wotawa

    • Opportunities for professional development and career advancement
    • Stable employer
    • Attractive campus environment with good public transportation connections
    • State-of-the-art research infrastructure
    • …and much more

Application Deadline:
Open until filled. Applications will be processed on a regular basis.  
Only full application documents will be considered
Our project is committed to increase the proportion of academic female faculty and, for this reason, especially welcomes applications by qualified women. If applicants are equally qualified, a woman will be given preference for this position.

How to Apply:
If you are interested in a position, please submit regular application documents including

  1. letter of motivation (detailing previous research achievements, research goals, career plans);
  2. a complete CV, including a list of previous scientific expertise, awards, grants, stays abroad, attended lectures, attended summer schools, attended workshops, skills, and publications (if applicable);
  3. abstract in English of the applicant’s MSc thesis, BSc thesis or of a research project;
  4. a complete list of completed studies and transcripts of all grades;
  5. contact details of two reference persons (at least one academic) willing to provide a recommendation letter;
  6. proof of proficiency in English (usually TOEFL/IELTS/CAE);

as described at the specific positions below.

 
Two PhD positions with Dr. Ozan Özdenizci:
We are looking for highly motivated students with a strong background and research interest in machine learning. The candidates will work on novel resource-efficient deep learning algorithms and architectures, with a focus on improving the reliability, safety, and resilience of AI systems. These positions will be engaged in one or more of the following areas: adversarial machine learning, privacy-preserving AI, efficient generative deep learning, hardware-centric learning for neural networks. The ideal candidates should have strong scientific drive, good programming skills (particularly in PyTorch or Jax), as well as evidence for excellent prior performance as a student. An interest in collaborating within a multidisciplinary team is necessary due to the project's interdisciplinary nature.

Duration: 4 years

Application: Submit the application documents as pdf files to the e-mail address oezdenizcinoSpam@tugraz.at, using the subject line "BILAI PhD Application".