PhD Position in Trustworthy Multimodal World Models for Critical Systems
Explore robust AI-driven simulations for critical systems using vision, graph, and tabular data.
Best for:Best for computer science PhD candidates with expertise in AI, machine learning, and programming, seeking to contribute to trustworthy AI systems for critical applications.
Overview
This PhD position focuses on developing trustworthy multimodal world models for critical simulations, combining vision, graph, and tabular data. The research will address foundational and generative AI techniques, with a strong emphasis on robustness and evaluation. The successful candidate will join the University of Luxembourg’s research team, contributing to cutting-edge work at the intersection of AI and critical systems. The role requires a strong background in computer science and proficiency in programming, with an interest in advancing AI reliability for high-stakes applications.
What you'll do
- Develop trustworthy multimodal world models integrating vision, graph, and tabular data for critical simulations.
- Conduct research on robustness and evaluation methodologies for AI-driven systems.
- Implement and test AI models using advanced programming and machine learning techniques.
- Collaborate with interdisciplinary research teams to advance AI reliability in high-stakes applications.
- Publish research findings in peer-reviewed conferences and journals.
- Present research progress at internal and external academic events.
Requirements
Degree required: Master of Science (MSc) in Computer Science or a related field
Degree offered: PhD
Language: English; proficiency required for academic communication and collaboration
Instruction: English
- Strong programming skills (e.g., Python, Java, C++)
- Expertise in machine learning and AI techniques
- Experience with computer vision and data integration
- Background in graph data analysis or related fields
- Familiarity with AI robustness and evaluation methodologies
- Open to international applicants
- No specific residency or nationality restrictions mentioned
Funding & terms
How to apply
Applicants should submit their CV, cover letter, and research statement via the manual application process. Additional documents may be requested based on the application review.
- CV
- Cover letter
- Research statement
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