Summary
The University of Vienna is offering a PhD position in Responsible AI within the newly formed Responsible Machine Learning (ML) Group at the Faculty of Computer Science. This is a unique opportunity to join an international academic team led by Prof. Dr. Martin Pawelczyk, focusing on cutting-edge research at the intersection of AI Safety and Data-Centric AI. The position aims to make large-scale machine learning more reliable, transparent, and aligned with human values, contributing to high-impact projects from the ground up.
Designation
PhD Researcher (Praedoc)
Job Details
| Category | Details |
|---|---|
| Job Vacancy Starting | October 15, 2026 |
| Working Hours | 30.00 hours per week |
| Classification CBA | §48 VwGr. B1 Grundstufe (praedoc) |
| Employment Duration | Limited contract until October 12, 2029 (initially 1.5 years, extendable to 3, and potentially up to 4 years based on progress) |
| Job ID | 6159 |
| Compensation | EUR 3,776.10 (full-time basis, 14 times a year, may increase with professional experience) |
Research Areas
The Responsible Machine Learning Group is particularly interested in the following areas:
- Data-Centric AI: Advancing machine unlearning, privacy-preserving techniques, and robust data curation.
- AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems.
- Efficiency: Streamlining large-scale model experimentation and training.
- Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale.
Specific focus for the PhD position includes:
- Data-Centric AI: Including data attribution, data curation, and privacy preservation for large foundation models (e.g., LLMs and VLMs).
- Agentic AI: Exploring multi-agent systems and their dynamics.
- Explainable AI: With a particular emphasis on mechanistic interpretability.
Location
University of Vienna, Vienna, Austria
Eligibility/Qualifications
Must-haves:
- A Master’s degree (completed or near completion) in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related quantitative field.
- A solid background in machine learning, statistics, and/or mathematics.
- Strong programming skills in Python.
- An early track record of research (e.g., a high-quality Master’s thesis, open-source contributions, or workshop papers).
- Excellent command of written and spoken English.
- A high degree of intrinsic motivation, curiosity, and the ability to work both independently and collaboratively.
Desirable skills:
- Proficiency in at least one major deep learning framework (e.g., PyTorch, JAX).
- Experience in training or fine-tuning large-scale models (LLMs, VLMs) in distributed settings.
- Familiarity with cluster computing environments (e.g., SLURM) and Linux-based workflows.
- Prior experience in a research lab, including contributions to publications or significant open-source projects.
- Teaching experience.
Scholarship Description
This PhD position offers a competitive full-time salary and the opportunity to pursue a doctoral thesis within a maximum of four years. As an early member of a fast-growing team, the successful candidate will contribute to shaping the research culture and working on high-impact projects. The scholarship includes access to over 600 free training and coaching courses to deepen skills. The University of Vienna provides an inspiring international academic atmosphere in Vienna, consistently ranked as one of the world’s most livable cities.
How to Apply
Applicants must submit the following documents:
- Academic curriculum vitae.
- Cover letter (stating earliest start date and motivation).
- A copy of your thesis (or an extended abstract if still in progress).
- Official transcripts for both Bachelor’s and Master’s degrees.
Additionally, applicants are encouraged to fill out this optional form: https://tinyurl.com/mvamwy7a
For questions, contact: Martin Pawelczyk at martin.pawelczyk@univie.ac.at
Last Date for Apply
September 18, 2026
