The University of Vienna is a community of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion and determination?
To strengthen our team, we are seeking a university assistant to develop advanced machine learning and artificial intelligence methods.
39 Faculty of Computer Science
Job vacancy starting: 10/01/2026 | Working hours: 30,00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc)
Limited contract until: 09/30/2030
Job ID: 5376
The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration.
The working group “Probabilistic and Interactive Machine Learning” within the research group “Data Mining and Machine Learning” at the Faculty of Computer Science, led by Prof. Sebastian Tschiatschek, develops foundational methods in machine learning and artificial intelligence. We focus particularly on the areas of reinforcement learning, interactive learning, and deep probabilistic models.
While modern reinforcement learning (RL) has achieved remarkable success, it remains limited when applied to complex, open-ended, or poorly defined environments. Two of the most critical bottlenecks in contemporary AI are sample inefficiency, often caused by the lack of intelligent, structured exploration, and the "reward engineering" problem, where designing an explicit scalar reward function that captures desired behavior is incredibly difficult or impossible.
Furthermore, as AI systems are deployed in more complex environments, the challenges of AI alignment (ensuring systems behave according to human preferences) and constrained learning (adhering to strict safety, legal, or physical boundaries) become important.
This position is dedicated to addressing these core challenges by advancing the frontiers of Inverse Reinforcement Learning (IRL), exploration, and safe/aligned AI.
You actively participate in research, teaching & administration, which means:
You will contribute to academic research projects in the above-mentioned areasThe following are also desirable:
Experience with research methods in the field of machine learning and artificial intelligence, as well as scientific writinWork-life balance: Our employees enjoy flexible working hours and can partially work remotely.
Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment.
Good public transport connections: Your workplace is easily accessible by public transport.
Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge.
Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis) increases if we can credit professional experience.
Tenure: The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration.
Sebastian Tschiatschek
sebastian.tschiatschek@univie.ac.at
We look forward to new personalities in our team!
The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates.
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Application deadline: 06/16/2026
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