Research Scientist - Computer Science & Computational Physics

About the Role

Role type: Contractor (flexible, Part-Time or Full-Time) micro1 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.

Responsibilities & Tasks

• 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.

Qualifications & Requirements

• 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.