Qualifications

• PhD or equivalent research experience in relevant fields such as Machine Learning or Physics.
• Strong publication record in advanced AI and generative modeling.
• Hands-on experience with transformer/diffusion architectures, particularly in structured contexts.
• Familiarity with formal representations like ontologies and typed graphs.
• Solid software engineering skills, particularly with Python and frameworks like PyTorch or JAX.
• Excellent written and verbal communication skills in English, enabling collaboration across various teams.

Responsibilities

• Develop advanced AI systems and world model reasoning algorithms.
• Create simulation environments and reinforcement learning strategies for robotics and mechatronics.
• Research neural generative reasoning with ontology-constrained representations.
• Design combinatorial and graph search methods using neural operators and deterministic solvers.
• Work on causal modeling and cross-domain constraint propagation in engineering ontologies.
• Generate and validate synthetic training data for safety-critical engineering scenarios.
• Contribute to the scientific community through internal and external publishing.

Benefits

• Emphasis on equal opportunities, inclusion, and diversity.
• Collaborative work environment with cross-disciplinary teams.
• Opportunity to significantly impact advanced AI research and applications.
• Access to resources for publishing and sharing research contributions.