TU Wien is Austria's largest institution of research and higher education in the fields of technology and natural sciences. With over 26,000 students and more than 4000 scientists, research, teaching, and learning dedicated to the advancement of science and technology have been conducted here for more than 200 years, guided by the motto "Technology for People". As a driver of innovation, TU Wien fosters close collaboration with business and industry and contributes to the prosperity of society.
The TU Wien Faculty of Informatics seeks to fill the open tenure-track position of an Assistant Professor (all genders) of Graph Machine Learning for 20 hours/week. The position is affiliated with both the Databases and Artificial Intelligence Unit, part of the Faculty of Informatics, and the ÖAW-AITHYRA- Research Institute for Biomedical Artificial Intelligence. The estimated starting date is June 2025.
The work contract is initially limited to six years. The candidate and TU Wien can agree upon a tenure evaluation, which when positive, opens the possibility to change the position to Associate Professor with an unlimited contract. TU Wien is among the most successful technical universities in Europe, and it is Austria’s largest scientific-technical research and educational institution. The Faculty of Informatics, one of the eight faculties at TU Wien, plays an active role in national and international research and has an excellent reputation. The main areas of research include Computer Engineering, Logic and Computation, Visual Computing & Human-Centered Technology, as well as Information Systems Engineering.
Aufgaben
We are looking for a candidate who will strengthen the profile of the Faculty of Informatics in Artificial Intelligence (AI) and Machine Learning (ML). The candidate is expected to work in AI and ML with a focus on graph machine learning, complementing the expertise of the Faculty of Informatics. The candidate will ideally establish collaborations with national and international institutions working on AI for Sciences. We expect the candidate to bridge the Faculty of Informatics with the AITHYRA Research Institute for Biomedical Artificial Intelligence. The following non-exhaustive list highlights some potential topics of a successful candidate:
- Design and development of novel graph machine learning architectures (e.g., graph neural networks, graph transformers)
- Design of novel methods for a wide array of tasks in graph machine learning, including node-level, link-level, and graph-level tasks
- Design of novel methods for critical life-science domains, including the biochemical domain (e.g., drug discovery)
- Graph foundation models: Development of foundation models for graphs by building on the success of large language models
- Theory of graph machine learning and geometric deep learning: symmetry, inductive bias, expressive power, generalization, extrapolation, convergence
- Logical foundations of graph machine learning: logic of graphs, descriptive complexity of graph neural networks, uniform expressiveness
- Interpretability and explainability of graph learning through logical methods
- Design of graph machine learning solutions for different types of graphs, ranging from simple graphs to knowledge graphs
- Adaptation of graph machine learning techniques to relational databases and associated tasks
A successful candidate should have a relevant postdoctoral experience and a compelling research vision. We expect publications in top-tier ML (NeurIPS, ICML, ICLR) and AI conferences (IJCAI, AAAI) as well as journal publications (AIJ, JAIR, JMLR, JAR).
We are particularly interested in candidates working in areas that will complement our existing expertise and lead to fruitful collaborations with other members of the Faculty of Informatics and TU Wien in general. The candidate is expected to serve as a bridge between symbolic AI and neural AI.Besides research, the duties of an Assistant Professor at TU Wien include graduate and undergraduate teaching (in English and German) as well as contributing to usual management and faculty service tasks.
Ihr Profil
Applicants are expected to have the following qualifications:
Essential
- PhD or doctoral degree in Computer Science, Mathematics, or related subjects
- Post-doctoral experience at a university or other research institution
- An outstanding research and publication record
- Excellent in written and spoken English
- Experience with scientific project collaborations
- Experience in university teaching both undergraduate and graduate
- Experience in supervision or co-supervision of doctoral students
- An excellent reputation as an active member of the international scientific community
- Pedagogical and didactic skills
- Administrative and organisational skills
Desirable
- Leadership skills
- Industrial experience and/or collaborations
- Experience in grant management
- If the candidat’s knowledge of German is not sufficient, the willingness to learn German is expected
Wir bieten
- Excellent working conditions in an international research environment
- An attractive salary, including additional contributions to a pension fund
- A mentoring program for assistant professors
- Support for relocating to Vienna (if required)
- A position in a city with an exceptional quality of life
- Additional benefits for employees can be found at the following link: Fringe-Benefit Catalogue of TU Wien
General information can be found at the following links:
- TU Wien
- Faculty of Informatics
- The 4 research foci of the Faculty of Informatics
- Databases and Artificial Intelligence Unit
- Institute of Logic and Computation
- AITHYRA- Research Institute for Biomedical Artificial Intelligence
- Living in Vienna
The minimum salary as half-time University Assistant is EUR 2.466,45 gross (14 x per year) according to the collective bargaining agreement for a PostDoc. After signing the qualification agreement, the minimum salary as half-time Assistant Professor is EUR 2.904,1 gross (14 x per year). We look forward to receiving your application until April 24th, 2025.
Applications have to include the following documents:
- A detailed curriculum vitae
- A letter of motivation
- A list of publications sorted by journals, conference papers, and other publications
- A teaching statement: 2 pages maximum
- A research statement: brief summary of past research activities, as well as a convincing outline of planned research activities, and an explanation of their contribution to the scientific profile of the Faculty of Informatics; 4-6 pages maximum; incl. abstract
- Certificates of doctoral and diploma degrees should be uploaded under the category: +add more documents
- Copies of the applicant’s three most important publications related to the position together with an explanation of their relevance should be also uploaded under the category: +add more documents
TU Wien is committed to increasing the proportion of women in particular in leadership positions. Female applicants are explicitly encouraged to apply. Preference will be given to women when equally qualified, unless reasons specific to a male applicant tilt the balance in his favour. People with special needs are equally encouraged to apply. In case of any questions, please contact the confidant for disabled persons at the university, Mr. Gerhard Neustätter.
If you have any questions, please do not hesitate to contact us Carmen Keck | T: +43 1 588 01 406201 Here you can find also relevant information about the application process.
