Research Scientist - Computer Science & Computational Physics

Role Type: Contractor (flexible, Part-Time or Full-Time)

Location: Remote Our team is engaging Research Scientists in Computer Science & Computational Physics to help advance a customer’s high-impact research project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required - your domain knowledge is what matters. Scope of Work Identify and propose open problems, new bounds, or tractable research challenges in your subfield for rigorous investigation. Conduct structured research using frontier AI models and agents to attempt proofs, develop algorithms, or run computational simulations. Systematically verify research outputs by checking proofs, reproducing numerical results, or employing formal tools. Assess findings for novelty and correctness in direct comparison with recent literature and published results. Document methodologies, partial results, and encountered challenges through clear and thorough written reports. Highlight promising new directions and discoveries for deeper exploration by senior research professionals.

Preferred Qualifications: Advanced standing in research: late-stage PhD candidate, postdoctoral researcher, or early-career academic (0-5 years post-PhD) in computer science or mathematical/computational physics. Recognized by peer community for research excellence, such as best paper or dissertation awards at leading venues (e.g., STOC, FOCS, SODA, PLDI, SC). Strong publication track record within the past three years, including multiple top-venue papers and recent results addressing named open problems or introducing novel concepts. Hands‑on expertise in computational methods, encompassing simulation, numerical analysis, and algorithmic implementation. Experience reviewing or sub-reviewing for prominent conferences in your specialty is a plus. Background in leveraging frontier models, agents, or formal computational tools (e.g., Lean, SAT/SMT solvers) in scholarly work. Publicly shared research statement or homepage outlining specific open problems currently under investigation.