Remote | Materials Scientist (Semiconductors & Molecular Modeling) — Up to $60/hour

We are sharing a specialised part-time consulting opportunity for PhD-level materials scientists with strong expertise in semiconductor materials, molecular modelling, scientific computing, and research-grade programming.

This role focuses on designing original, executable computational problems based on authentic materials science research workflows. Selected experts will develop challenging coding-based tasks, create rigorous reference solutions and grading criteria, and test and refine problems until they require genuine research-level scientific and computational reasoning.

Key Responsibilities

Materials Science Problem Design

• Develop original research-level computational problems in materials science
• Build tasks from published papers, public datasets, open-source repositories, or independently designed scientific scenarios
• Create problems requiring multi-step scientific and computational reasoning
• Ensure tasks reflect realistic research workflows rather than standard textbook exercises
• Design problems with scientifically defensible and reproducible solutions

Semiconductor Materials

• Develop computational tasks involving semiconductor materials and their properties
• Create problems requiring analysis of structure-property relationships and material behaviour
• Incorporate realistic modelling assumptions, physical constraints, and material parameters
• Design tasks requiring interpretation of simulation or experimental-style outputs
• Apply deep semiconductor materials expertise to task validation and difficulty calibration

Molecular Modeling

• Create problems involving molecular and atomistic modelling
• Develop workflows requiring simulation, structural analysis, or quantitative interpretation
• Evaluate modelling assumptions, boundary conditions, parameters, and numerical outputs
• Incorporate realistic edge cases and computational limitations
• Ensure tasks require genuine understanding of molecular modelling methods

Scientific Computing & Programming

• Write and validate scientific workflows using Python, R, or another relevant programming language
• Develop computational setups, reference calculations, and validation scripts
• Debug numerical, modelling, and implementation issues
• Build reproducible workflows suitable for automated evaluation
• Ensure code accurately implements the underlying scientific problem

Research Task Development

• Source appropriate scientific material from papers, datasets, repositories, or original scenarios
• Translate complex research material into clearly specified computational tasks
• Define inputs, assumptions, constraints, and expected outputs
• Create assignments requiring both materials expertise and coding proficiency
• Ensure difficulty arises from scientific reasoning rather than unnecessary complexity

Reference Solutions & Grading Criteria

• Produce authoritative reference solutions and supporting calculations
• Define clear criteria describing what constitutes a correct solution
• Identify essential scientific reasoning steps and computational outputs
• Develop grading logic capable of distinguishing correct solutions from plausible but flawed approaches
• Ensure evaluation standards remain precise and reproducible

Testing & Difficulty Calibration

• Test tasks against advanced computational systems
• Analyse common scientific, numerical, and reasoning failure modes
• Refine prompts, inputs, constraints, and expected outputs based on testing
• Adjust difficulty while preserving scientific validity
• Finalise tasks only when they reliably require advanced materials science expertise

Research Engineering Workflow

• Work through a Git/GitHub pull-request workflow
• Run and validate code within Docker-based environments
• Respond to automated quality checks and reviewer feedback
• Maintain clean, reproducible code and supporting documentation
• Collaborate effectively within structured scientific software workflows

Ideal Profile

• 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

Engagement Details

• Part-time independent contractor engagement
• Fully remote
• 20+ hours per week
• Initial duration of approximately 6 weeks
• Immediate start
• Compensation: Up to $60/hour
• Work includes materials science problem design, scientific coding, reference-solution development, grading criteria, testing, and task refinement
• Projects may be extended, shortened, or concluded based on project needs and performance
• Work must be completed 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

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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