Principal Scientific Research Expert
Pubblicato il 20-10-2026 - Jobgether in Campo di Ne
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Principal Scientific Research Expert – Computational Theory & Physics based in Italy.
Join an advanced AI research initiative at the intersection of computational theory, physics, mathematics, and artificial intelligence. As a Principal Scientific Research Expert, you will tackle complex open research problems and guide advanced AI models and agents through rigorous scientific investigations. You will evaluate theoretical breakthroughs, validate computational results, and distinguish genuine scientific progress from plausible but unverified conclusions. Working across mathematical proofs, algorithm development, numerical experiments, simulations, and high-performance computing, you will help establish robust standards for scientific evaluation. This remote opportunity offers experienced researchers the chance to influence how frontier AI systems approach challenging scientific questions. Your expertise will shape research priorities,
strengthen evaluation methodologies, and uncover promising directions for future discovery.
Accountabilities
- Identify and formulate foundational open research problems, theoretical limits, and computational challenges where meaningful progress can be rigorously measured.
- Guide advanced AI models and agents through complex, multi-stage research workflows involving mathematical proofs, algorithm design, numerical experiments, simulations, and high-performance computing.
- Validate scientific findings through proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques.
- Assess the novelty, correctness, and scientific significance of research outputs by comparing them with established findings and current scientific literature.
- Produce concise, structured research memos documenting attempted solutions, partial progress, methodological limitations, recurring