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

Requirements

• 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