Principal Research Scientist (Computer Science / Computational Physics)

Research scope

Work at the intersection of computational theory and AI, helping define verifiable progress on open scientific problems. The role combines research direction with rigorous review of model generated proofs, algorithms, experiments and simulations.

This is a remote contractor engagement with flexible part time or full time options. Prior AI experience is not required.

What you'll do

• Identify and clearly frame foundational open problems, theoretical bounds and simulation challenges.
• Guide models and agents through research processes involving proofs, algorithms, numerical experiments and high performance simulations.
• Validate results through proof checks, computational reproduction and formal methods, identifying where generated reasoning fails.
• Assess novelty, correctness and significance against current literature and established results.
• Write concise research memos describing attempts, partial solutions, model limitations and recurring failures.
• Recommend promising subfields and problems suited to investigation with AI and computational tools.

Preferred research background

The preferred profile includes roughly seven to ten or more years of active research in computer science or mathematical or computational physics, with substantial scholarly contributions. Field recognition may include major prizes, society fellowships or plenary and invited talks at prominent scholarly events.

• A consistent publication record in leading venues, including results from the past year.
• Success resolving named open problems or developing influential concepts adopted by peers.
• Practical expertise in simulation, numerical analysis, algorithm implementation or high performance computing.
• The ability to examine technical work rigorously beyond your immediate specialty.

Program committee or editorial board experience is a strong plus. Experience with formal tools such as Lean, Coq or SAT/SMT solvers, a public record of outlining open problems, or research demonstrations using advanced AI systems is also valuable.