The University of Vienna is a community of more than 10,000 people, including approximately 7,500 faculty members, passionately seeking answers to the deep questions that will shape our future. They represent individuals driven by curiosity and the constant pursuit of excellence. Together with us, they will find space to try things and expand their possibilities. Are you inspired by their passion and determination? We're hiring now
University PhD Assistant – Research Group DM & ML
39 Department of Computer Science
start date: February 1, 2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstuve (Praed)
Limited to: 2030.01.31
Reference number: 4938
At the University of Vienna, more than 7,500 academics are continuously engaged in curiosity-driven exploration that helps us better understand our world. Does this sound like you? Then join our skilled team!
Your personal sphere of influence:
The working group “Probabilistic and Interactive Machine Learning'' within the research group “Data Mining and Machine Learning'' of the Faculty of Computer Science, led by Professor Tschiatschek, develops methods for machine learning and artificial intelligence, particularly in the areas of reinforcement learning and deep probabilistic models.
To strengthen our team, we are seeking a university assistant to develop advanced machine learning techniques to improve simulation and optimization of distributed systems, including specializing neural ODEs and their training routines.
This research addresses the challenges posed by the energy transition, which transforms electrical power systems (EPS) into low-inertia, highly digitalized power electronics-driven architectures with increasing interdependence of component and system dynamics. Traditional simulation and optimization approaches that separate EPS analysis and simulation by timescale and partition them into independent zones with independent models and solvers are no longer sufficient.
From real-time operations management to long-term planning for optimization and expansion, tackling new challenges across timescales requires new methodologies. This creates a demand for fast and flexible modeling frameworks such as surrogate models, physically informed neural networks, neural ODEs, and other hybrid physics and ML approaches to accelerate high-fidelity simulations.
The employment contract period is 4 years. Initially limited to 1.5 years, the employment relationship will be automatically extended to 4 years if the employer does not issue a non-renewal notice within the first 12 months.
Future challenges:
You will be actively involved in research, education, and administration.
- Participation in research projects/scientific research Participation in publications/scientific papers/lecture activities
- Participation in conferences and publication of research results in journals and conferences
- Signing a thesis contract within 12 months (if not already signed)
- Participation in courses and independent instruction in accordance with the provisions of the collective agreement
- student supervision
- Participation in organizing meetings, conferences, and symposiums
- Participation in laboratory management, education, and research
Requirements:
- Completed a master's degree (or equivalent) in computer science, mathematics, electrical engineering, information processing, or related field.
- High analytical ability
- Experience in interdisciplinary research fields
- Advanced written and oral communication skills
- Very good written and spoken English skills
- IT user skills
- Collaborative, team oriented, proactive behavior
- Strong knowledge in the areas of human-computer interaction, explainable AI, qualitative research, and interview research planning and implementation.
- Outstanding academic work, especially first publications in the field of explainable AI focused on understanding algorithms by different stakeholders, such as ACM FAccT, ACM AIES, International Journal of Human-Computer Studies, etc.
- Excellent written and oral communication skills
It is also desirable that:
- Teaching experience
- Knowledge of university processes and structures
- Overseas experience
What we offer:
Work-life balance: Our employees enjoy flexible working hours and can work partially remotely.
A stimulating work environment: You will be part of an international academic team in a healthy and fair working environment.
Good public transport links: The workplace is easily accessible by public transport.
Further in-house training and coaching: Opportunity to continually develop your skills. There are over 600 courses to choose from for free.
Fair pay: If specialized experience is recognized, the basic salary will increase to 3714,80 euros (on a full-time basis).
Equal opportunities for all: We welcome any additions/new personalities to our team!
It's very easy to apply:
- Cover letter/motivation letter. In particular, please briefly explain your aptitude and previous knowledge regarding telephone calls (maximum 2 pages)
- Academic background/motivation statement (including description of educational experience, if available)
- List of publications
- Proof of teaching experience (if available)
- degree certificate
- Apply from the job portal / Apply now button
If you have any questions, please contact us below.
Sebastian Ciacek
sebastian.tschiatschek@univie.ac.at
We look forward to adding new personalities to our team.
The University of Vienna has an anti-discriminatory employment policy and is committed to equal opportunities, the empowerment of women and diversity. We have a particular focus on increasing the number of women in senior and academic positions among the university's faculty and general staff, and we explicitly encourage qualified women to apply. Preference will be given to female candidates in consideration of equivalent qualifications.
University of Vienna. A space for individuality. Since 1365.
data protection
Application deadline: 2025/12/08
Prae Doc
