Is the Job related to staff position within a Research Infrastructure?: No
Offer Description
The Doctoral Candidate will be employed for 36 months as part of the "Generative Explainee-aware Explainability and Transparency in Proactive Cyber-Physical Eco-Environments (GREET)" project, funded by Horizon Europe under the Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks, Grant No. 101226624. The Doctoral Candidate will be enrolled in the PhD program at Vienna University of Technology (TU Wien), Faculty of Informatics, with the 36-month appointment based at AVL in Graz, Austria, under conditions aligned with MSCA regulations for Doctoral Candidates.
GREET (Generative Explainee-aware Explainability and Transparency in Proactive Cyber-Physical Eco-Environments) is a European doctoral network comprising 13 academic and industrial partners across nine countries. The network brings together expertise in AI explainability, transparency, cyber-physical systems, and advanced software engineering. Doctoral Candidates benefit from a coordinated training program combining research, industry exposure, and transferable skills development while working on advanced AI technologies in an international, collaborative environment.
As a Doctoral Candidate at AVL, you will conduct research in Computational Engineering, focusing on the autonomous generation and optimization of engineering designs through generative AI and computational search techniques. Your work will develop methods for exploring vast design spaces, evaluating engineering feasibility, and synthesizing solutions to complex automotive design and system optimization problems.
Where to apply
Website: https://jobs.avl.com/job-invite/39302/
Apply now
Requirements
Research Field: Computer science » Other
Education Level: Master Degree or equivalent
Skills/Qualifications
YOUR RESPONSIBILITIES:
- Development of generative AI models for autonomous design space exploration in automotive engineering
- Computational methods for evaluating and optimizing engineering designs against multiple constraints and objectives
- Integration of symbolic and learning-based approaches for rule-based engineering formulation and synthesis
- Application of generative techniques to physical design problems (components, structures, systems in powertrain and vehicle development)
- Collaboration with academic partners on explainability and transparency in generative AI systems
YOUR PROFILE:
- Completed education (University or University of Applied Sciences, University of Technology, or comparable) with a focus on Computer Science, Software Engineering, or a closely related discipline, with completion by August 2026 at the latest and eligibility for admission to a doctoral program are required
- Strong foundational knowledge in Large Language Models, AI agents, machine learning, software architecture, or cyber-physical systems
- Experience in LLM/RAG software development with Python and SQL; Rust or comparable systems-level programming skills are an advantage
- Ability to work independently and collaborate effectively in interdisciplinary teams
- Very good knowledge in English
Languages: ENGLISH
Level: Excellent
Additional Information
Benefits
WE OFFER:
- Various working time models, flextime and the possibility of working from home
- Contributing to a safer and more sustainable future of mobility
- Food trucks, snack bar and canteen with freshly cooked daily menus
- Events, e.g. summer festival, Oktoberfest, AVL Christmas parties or after-work events
- Personalized onboarding process including a mentoring system
Work Location(s)
Number of offers available: 1
Company/Institute: AVL List GmbH
Country: Austria
Geofield
Contact
State/Province: Styria
City: Graz
Website: https://www.avl.com/
Street: Hans-list-Platz 1
Postal Code: 8010
