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.
Lead rigorous AI-assisted scientific research by formulating open problems, validating theoretical and computational results, and setting standards for distinguishing genuine progress from unsupported claims.
Guide AI-assisted scientific research by formulating open problems, validating theoretical and computational results, assessing scientific significance, and setting rigorous standards for measuring progress.
Guide AI-assisted research in computational theory and physics by formulating open problems, validating proofs and computational results, assessing scientific contributions, and setting rigorous standards for measuring progress.
Lead biologics process development and clinical manufacturing readiness across analytical sciences, purification, formulation, and bioconjugation, guiding technical teams, external partners, and regulatory work.
Lead research into useful fault-tolerant quantum applications by designing algorithms, building implementations, and quantifying logical resource needs and credible paths to quantum advantage.
