진학프로석·박사 채용 접수 플랫폼

The Neuro-Symbolic AI Group at the IDIAP Research Institute operates at the interface between neural and symbolic AI methods aiming to enable the next generation of explainable, data-efficient and safe AI systems. Our research investigates how the combination of latent and explicit data representation paradigms can deliver better learning and reasoning over data.

We are looking for a Postdoctoral Researcher for an initial project of 24 months (extendable depending on funds).

In partnership with a leading company in the field of Hardware verification, we aim to develop a neuro-symbolic AI platform to convert informal digital design specifications into formally checkable verification artifacts, with logical rigor, traceability, and iterative validation. The project combines the generalization capabilities of large language models with symbolic constraints and formal verification backends to ensure generated properties are auditable, consistent, and correct-by-construction (or corrected via proof/counterexample feedback).

You will lead research and prototyping of neuro-symbolic methods that translate heterogeneous requirements (text, tables, diagrams) into structured representations and formally checkable properties. This includes designing controlled reasoning pipelines that combine LLMs with symbolic constraints (typed logical forms, DSL/IR design, constrained decoding), integrating formal feedback loops (SAT/SMT/model checking, counterexample- and proof-guided refinement), and developing mechanisms for semantic consistency, assumption management, and end-to-end traceability from specification fragments to generated SVAs and solver outcomes.

You will also help define benchmarks and evaluation protocols (correctness, robustness, coverage), publish at top-tier AI/ML venues, and contribute high-quality research code.

Application deadline: 30th January 2026