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
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Develop original research-level computational problems in materials science
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Build tasks from published papers, public datasets, open-source repositories, or independently designed scientific scenarios
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Create problems requiring multi-step scientific and computational reasoning
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Ensure tasks reflect realistic research workflows rather than standard textbook exercises
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Design problems with scientifically defensible and reproducible solutions
Semiconductor Materials
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Develop computational tasks involving semiconductor materials and their properties
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Create problems requiring analysis of structure-property relationships and material behaviour
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Incorporate realistic modelling assumptions, physical constraints, and material parameters
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Design tasks requiring interpretation of simulation or experimental-style outputs
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Apply deep semiconductor materials expertise to task validation and difficulty calibration
Molecular Modeling
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Create problems involving molecular and atomistic modelling
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Develop workflows requiring simulation, structural analysis, or quantitative interpretation
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Evaluate modelling assumptions, boundary conditions, parameters, and numerical outputs
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Incorporate realistic edge cases and computational limitations
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Ensure tasks require genuine understanding of molecular modelling methods
Scientific Computing & Programming
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Write and validate scientific workflows using Python, R, or another relevant programming language
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Develop computational setups, reference calculations, and validation scripts
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Debug numerical, modelling, and implementation issues
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Build reproducible workflows suitable for automated evaluation
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Ensure code accurately implements the underlying scientific problem
Research Task Development
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Source appropriate scientific material from papers, datasets, repositories, or original scenarios
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Translate complex research material into clearly specified computational tasks
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Define inputs, assumptions, constraints, and expected outputs
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Create assignments requiring both materials expertise and coding proficiency
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Ensure difficulty arises from scientific reasoning rather than unnecessary complexity
Reference Solutions & Grading Criteria
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Produce authoritative reference solutions and supporting calculations
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Define clear criteria describing what constitutes a correct solution
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Identify essential scientific reasoning steps and computational outputs
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Develop grading logic capable of distinguishing correct solutions from plausible but flawed approaches
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Ensure evaluation standards remain precise and reproducible
Testing & Difficulty Calibration
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Test tasks against advanced computational systems
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Analyse common scientific, numerical, and reasoning failure modes
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Refine prompts, inputs, constraints, and expected outputs based on testing
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Adjust difficulty while preserving scientific validity
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Finalise tasks only when they reliably require advanced materials science expertise
Research Engineering Workflow
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Work through a Git/GitHub pull-request workflow
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Run and validate code within Docker-based environments
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Respond to automated quality checks and reviewer feedback
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Maintain clean, reproducible code and supporting documentation
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Collaborate effectively within structured scientific software workflows
Ideal Profile
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PhD required in Materials Science, Materials Engineering, Applied Physics, Chemistry, Chemical Engineering, or a closely related field
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Demonstrated expertise in both semiconductor materials and molecular modeling
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Strong working proficiency in Python, R, or another scientific programming language
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Hands-on experience using scientific code for materials modelling, simulation, numerical analysis, or computational research
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Comfortable with Git/GitHub
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Experience running code in Docker or other containerised environments
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Strong understanding of reproducible scientific computing
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Ability to translate advanced materials research into clearly defined computational problems
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Peer-reviewed publications are highly valued
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Prior scientific software or research engineering experience is advantageous
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Strong written communication and ability to document scientific assumptions, methods, and solutions precisely
Engagement Details
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Part-time independent contractor engagement
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Fully remote
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20+ hours per week
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Initial duration of approximately 6 weeks
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Immediate start
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Compensation: Up to $60/hour
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Work includes materials science problem design, scientific coding, reference-solution development, grading criteria, testing, and task refinement
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Projects may be extended, shortened, or concluded based on project needs and performance
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
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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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