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Company Description:
MillionLogics is a trusted Oracle Partner and global leader in IT solutions, with operations in London, UK, and a development hub in Hyderabad, India. Specialising in innovative and scalable services, MillionLogics empowers enterprises through data & AI, cloud solutions, IT consulting, and custom application development. With a team of 85+ AI/ML experts, we deliver tailored solutions that foster digital transformation and operational excellence. We committed to client success. We blend world-class technical expertise with strategic insight to deliver results.
Role Overview
We are seeking a highly analytical and computationally proficient individual to join our team with a strong research background. You will be instrumental in contributing to this role by either crafting challenging and insightful problems in your respective research domain, devising elegant computational solutions.
Offer Details:
Required Skills:
- PhD or PhD Candidates in Computational Material science (Semiconductor materials and Molecular modeling)
- Has published at least 1 peer-reviewed paper
- Advanced proficiency in Python programming for scientific coding is preferred
- Excellent analytical, logical thinking, and problem-solving skills
- Strong written and verbal communication skills for clear documentation and collaboration
Responsibilities:
1. 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.
2. 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.
Additional Details
How to Apply : Please apply over LinkedIn or send us your updated CV to [Confidential Information] with email subject : 78723 – Material Science
Job ID: 148485717
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