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Gramian Consulting Group

Principal Scientific Research Expert - Computational Theory & Physics

Posted 2 Days Ago
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Remote
Hiring Remotely in Canada
Expert/Leader
Remote
Hiring Remotely in Canada
Expert/Leader
Lead rigorous research involving frontier AI models, theoretical computer science, computational physics, mathematical proofs, algorithms, numerical experiments, simulations, and high-performance computing. Evaluate research outputs for correctness, novelty, reproducibility, and significance; identify limitations and reasoning failures; document findings in concise research memos; and recommend promising open problems and research directions. The role requires independent judgment, strong scholarly contributions, deep computational research expertise, and excellent technical communication.
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About Gramian

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

About the Role

We are seeking an accomplished Scientific Research Expert with deep expertise in computer science, computational physics, or related theoretical and mathematical disciplines to contribute to an advanced AI research project. In this role, you will work with frontier AI models and agents to investigate open research problems, evaluate theoretical and computational results, and establish rigorous standards for measuring scientific progress. You will help guide multi-step research workflows involving proofs, algorithms, numerical experiments, simulations, and high-performance computing, while documenting model limitations and identifying promising directions for further investigation. Prior AI industry experience is not required; exceptional research expertise and rigorous scientific judgment are the priorities.

SENIORITY: Principal / Research Leader

LANGUAGE: Excellent written English

LOCATION: Remote — Worldwide

Key Responsibilities

  • Identify and formulate foundational open problems, theoretical bounds, and computational challenges where progress can be rigorously demonstrated.

  • Guide AI models and agents through complex, multi-step research workflows involving mathematical proofs, algorithm development, numerical experiments, and high-performance simulations.

  • Validate research results using proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques.

  • Assess the novelty, correctness, and scientific significance of research outputs against established findings and current literature.

  • Prepare concise research memos documenting attempted solutions, partial progress, model limitations, and recurring reasoning failures.

  • Recommend promising research directions, subfields, and open problems suitable for investigation using advanced AI models and computational tools.

  • Apply critical judgment when reviewing technical work beyond your immediate research specialization.

  • Help establish evaluation standards that distinguish genuine scientific progress from plausible but unsupported results.


Requirements
  • Approximately 7–10+ years of active research experience in computer science, mathematical physics, computational physics, or a closely related discipline.

  • Strong record of scholarly contributions, including publications in leading conferences, journals, or other recognized research venues.

  • Deep hands-on experience with computational research methods, such as numerical analysis, simulation, algorithm implementation, or high-performance computing.

  • Demonstrated ability to evaluate technical claims rigorously, verify results, and identify gaps in mathematical or computational reasoning.

  • Strong familiarity with the research literature and established results in your field.

  • Excellent analytical, technical writing, and research communication skills.

  • Ability to work independently, assess ambiguous problems, and communicate findings clearly.

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