Research Scientist - Computational Materials (Scientific Coding)

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. Role Overview We are looking for a highly analytical and research-driven individual with a strong background in Computational Materials to contribute to advanced AI evaluation initiatives. In this role, you will design and solve research-grade quantitative problems , supporting the development and evaluation of next-generation AI systems. You’ll work at the intersection of scientific computing, mathematical modeling, and AI reasoning , contributing to high-impact projects with leading AI organizations. Responsibilities: Quantitative Problem Design and Solutioning: Develop and conceptualize original, research-grade or graduate-level scientific problems with scientific coding/ programming, using Python. Rigorously define problem categories, secondary tags, and assign appropriate difficulty levels. Rigorously solve formulated problems using sound principles, ensuring absolute accuracy, reliability, and logical coherence of the solution path. Quality Assurance & Collaboration: Actively participate in two-tier reviews, meticulously evaluating both accuracy of problems and solutions. Collaborate effectively with reviewers and team leads, demonstrating a proactive approach to incorporating feedback, refining content, and enhancing overall quality promptly. Commitments Required: 8 hours per day with an overlap of 4 hours with PST. Employment type: Contractor assignment (no medical/paid leave) Duration of contract: 4 weeks Location: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Kenya, Nigeria,Turkey, Vietnam Selection process: Home Assignment PhD or PhD Candidate in Computational Materials , Semiconductor materials, Molecular modeling, or similar At least one peer-reviewed publication in a relevant domain Proficiency in Python for scientific computing (e.g., NumPy, SciPy, or similar) Strong analytical thinking and problem-solving skills Ability to clearly document complex mathematical reasoning and solutions