Materials Scientist – Semiconductors, Molecular Modeling

Job not on LinkedIn

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🗽 New York – Remote

🗽 New York – Remote

💵 $60 / hour

⏱ Part Time

🟡 Mid-level

🟠 Senior

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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24-MAG

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤝 B2B

💼 Consulting

B2B • Consulting

24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.

📋 Description

• Develop original research-level computational problems in materials science • Build tasks from published papers, public datasets, open-source repositories, or independently designed scientific scenarios • Design semiconductor materials tasks involving structure-property relationships, material behaviour, modelling assumptions, physical constraints, parameters, and simulation or experimental-style outputs • Create molecular and atomistic modelling problems involving simulation, structural analysis, quantitative interpretation, boundary conditions, numerical outputs, edge cases, and computational limitations • Write and validate scientific workflows using Python, R, or another relevant programming language • Develop computational setups, reference calculations, validation scripts, and reproducible workflows for automated evaluation • Debug numerical, modelling, and implementation issues • Translate complex research material into clearly specified computational tasks with defined inputs, assumptions, constraints, and expected outputs • Produce authoritative reference solutions, supporting calculations, grading criteria, and reproducible evaluation logic • Test tasks against advanced computational systems and analyse scientific, numerical, and reasoning failure modes • Refine prompts, inputs, constraints, expected outputs, and difficulty while preserving scientific validity • Work through Git/GitHub pull-request workflows • Run and validate code in Docker-based environments • Respond to automated quality checks and reviewer feedback • Maintain clean, reproducible code and supporting documentation • Collaborate within structured scientific software workflows

🎯 Requirements

• PhD required in Materials Science, Materials Engineering, Applied Physics, Chemistry, Chemical Engineering, or a closely related field • Demonstrated expertise in both semiconductor materials and molecular modeling • Strong working proficiency in Python, R, or another scientific programming language • Hands-on experience using scientific code for materials modelling, simulation, numerical analysis, or computational research • Comfortable with Git/GitHub • Experience running code in Docker or other containerised environments • Strong understanding of reproducible scientific computing • Ability to translate advanced materials research into clearly defined computational problems • Peer-reviewed publications are highly valued • Prior scientific software or research engineering experience is advantageous • Strong written communication and ability to document scientific assumptions, methods, and solutions precisely • Must work without using confidential or proprietary information belonging to any employer, client, institution, or other third party • H1-B and STEM OPT support is unavailable for this engagement

🏖️ Benefits

• Part-time independent contractor engagement • Fully remote • 20+ hours per week • Initial duration of approximately 6 weeks • Immediate start • Projects may be extended, shortened, or concluded based on project needs and performance