Principal Research Scientist (Computer Science / Computational Physics)

Micro1; India; Remote; INR 11,268,000 - 19,718,000; Part time

Job summary

Cashback24x7 is seeking a Principal Research Scientist (Computer Science / Computational Physics) for a remote contractor role. You will contribute to an advanced customer project at the intersection of computational theory and AI, shaping how models learn, reason, and perform.

You will work with frontier AI models and agents to tackle open problems, drive research direction, and define standards for breakthroughs. A strong domain knowledge matters; no prior AI experience is required.

Qualifications

• 7–10+ years of active research in computer science or mathematical/computational physics.
• Record of scholarly contributions and recognized field-level achievements.

Responsibilities

• Identify open problems and theoretical bounds for verifiable progress.
• Guide AI models in multi-step research processes.
• Critically assess results using proof checks and numerical experiments.
• Document novelty and significance relative to literature.
• Produce research memos detailing attempts and limitations.
• Advise on promising subfields for AI-assisted research.

Skills

Computational research

Numerical analysis

High-performance computing

AI model evaluation

Theoretical proofs

Cross-disciplinary collaboration

Education

10+ years active research in CS/Math/Computational Physics

Strong publication record

PhD or equivalent research track

Tools

Lean

Coq

SAT/SMT solvers

Python/NumPy

Job description

Job Description

Role Title: Principal Research Scientist (Computer Science / Computational Physics)

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

Location: Remote

micro1 is engaging Principal Research Scientist (Computer Science / Computational Physics)s to contribute to an advanced customer project at the intersection of computational theory and AI. 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. You will work with frontier AI models and agents to tackle open problems, drive research direction, and define standards for scientific breakthroughs. Your insights and rigorous approach will be pivotal in charting what counts as genuine progress within your subfield.

Scope of Work

• Identify, frame, and articulate foundational open problems, theoretical bounds, or simulation challenges where verifiable progress can be demonstrated.
• Guide AI models and agents in multi-step research processes—ranging from proofs and algorithms to numerical experiments and high-performance simulations.
• Critically assess and validate results, utilizing proof checks, computational reproduction, and formal methods to pinpoint the limits of model-generated reasoning.
• Evaluate and document the novelty, correctness, and significance of research outputs relative to current literature and established results.
• Produce clear, concise research memos detailing research attempts, partial solutions, and observed model limitations or failure patterns.
• Advise on research directions, recommending promising subfields and open problems suitable for advancement via AI models and computational tools.

Preferred Qualifications

• 7 - 10+ years of active research in computer science or mathematical/computational physics, with a strong record of scholarly contributions.
• Recognition at the field level—such as major prizes, society fellowships, or plenary/invited talks at top scholarly events.
• A consistent publication record in leading venues within your domain, with recent results published in the past year.
• Demonstrated success resolving named open problems or introducing influential concepts adopted by peers.
• Deep, hands-on experience with computational research methods: simulation, numerical analysis, algorithmic implementation, and/or high-performance computing environments.
• Proven ability to rigorously examine technical work outside your immediate area of expertise.
• Experience on program committees, editorial boards, or with formal research tools (e.g., Lean, Coq, SAT/SMT solvers) is a strong plus, as is a public record of outlining open problems or showcasing research with advanced AI systems.