{"html":"<p>Role Title: Research Scientist - Computer Science &amp; Computational Physics</p><p>Role Type: Contractor (flexible, Part-Time or Full-Time)</p><p>Location: Remote</p><p>micro1 is engaging Research Scientists in Computer Science &amp; 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.</p><p>Scope of Work</p><ul><li>Identify and propose open problems, new bounds, or tractable research challenges in your subfield for rigorous investigation.</li><li>Conduct structured research using frontier AI models and agents to attempt proofs, develop algorithms, or run computational simulations.</li><li>Systematically verify research outputs by checking proofs, reproducing numerical results, or employing formal tools.</li><li>Assess findings for novelty and correctness in direct comparison with recent literature and published results.</li><li>Document methodologies, partial results, and encountered challenges through clear and thorough written reports.</li><li>Highlight promising new directions and discoveries for deeper exploration by senior research professionals.</li></ul><p>Preferred Qualifications</p><ul><li>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.</li><li>Recognized by peer community for research excellence, such as best paper or dissertation awards at leading venues (e.g., STOC, FOCS, SODA, PLDI, SC).</li><li>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.</li><li>Hands-on expertise in computational methods, encompassing simulation, numerical analysis, and algorithmic implementation.</li><li>Experience reviewing or sub-reviewing for prominent conferences in your specialty is a plus.</li><li>Background in leveraging frontier models, agents, or formal computational tools (e.g., Lean, SAT/SMT solvers) in scholarly work.</li><li>Publicly shared research statement or homepage outlining specific open problems currently under investigation.</li></ul>"}