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Contractual Remote Grading Papers Jobs (NOW HIRING)

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional ... Grading may entail grading exams, quizzes, homework, papers, and any other assignments.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional ... Grading may entail grading exams, quizzes, homework, papers, and any other assignments.

... paper, raw materials and transport & automotive. Founded in 1867, the company today has around 20 ... Ensures work is performed in accordance with contractual requirements, schedule, safety and quality ...

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Contractual Remote Grading Papers information

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$5

$14

$28

How much do contractual remote grading papers jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for contractual remote grading papers in the United States is $14.97, according to ZipRecruiter salary data. Most workers in this role earn between $7.21 and $20.19 per hour, depending on experience, location, and employer.

What is the difference between Contractual Remote Grading Papers vs Contractual Remote Content Reviewers?

AspectContractual Remote Grading PapersContractual Remote Content Reviewers
CredentialsEducational qualifications, often a degree in education or related fieldExperience in content moderation, sometimes certifications in digital content management
Work EnvironmentRemote, flexible hours, often independentRemote, may require monitoring tools, flexible hours
Industry UsageEducational institutions, testing agencies, online education platformsMedia companies, social media platforms, online content providers

Both roles are remote and require specific credentials, but Grading Papers focuses on evaluating student work, while Content Reviewers assess online content for compliance and quality. Understanding these differences helps job seekers find the right fit based on skills and industry interests.

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Infographic showing various Contractual Remote Grading Papers job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $31,138 per year, or $15 per hour.

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

24-MAG LLC

Manhattan, NY โ€ข On-site, Remote

$60/hr

Part-time, Contractor

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Remote | Materials Scientist (Semiconductors & Molecular Modeling)New York, New York, United StatesWe 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 ResponsibilitiesMaterials Science Problem DesignDevelop original research-level computational problems in materials scienceBuild tasks from published papers, public datasets, open-source repositories, or independently designed scientific scenariosCreate problems requiring multi-step scientific and computational reasoningEnsure tasks reflect realistic research workflows rather than standard textbook exercisesDesign problems with scientifically defensible and reproducible solutionsSemiconductor MaterialsDevelop computational tasks involving semiconductor materials and their propertiesCreate problems requiring analysis of structure-property relationships and material behaviourIncorporate realistic modelling assumptions, physical constraints, and material parametersDesign tasks requiring interpretation of simulation or experimental-style outputsApply deep semiconductor materials expertise to task validation and difficulty calibrationMolecular ModelingCreate problems involving molecular and atomistic modellingDevelop workflows requiring simulation, structural analysis, or quantitative interpretationEvaluate modelling assumptions, boundary conditions, parameters, and numerical outputsIncorporate realistic edge cases and computational limitationsEnsure tasks require genuine understanding of molecular modelling methodsScientific Computing & ProgrammingWrite and validate scientific workflows using Python, R, or another relevant programming languageDevelop computational setups, reference calculations, and validation scriptsDebug numerical, modelling, and implementation issuesBuild reproducible workflows suitable for automated evaluationEnsure code accurately implements the underlying scientific problemResearch Task DevelopmentSource appropriate scientific material from papers, datasets, repositories, or original scenariosTranslate complex research material into clearly specified computational tasksDefine inputs, assumptions, constraints, and expected outputsCreate assignments requiring both materials expertise and coding proficiencyEnsure difficulty arises from scientific reasoning rather than unnecessary complexityReference Solutions & Grading CriteriaProduce authoritative reference solutions and supporting calculationsDefine clear criteria describing what constitutes a correct solutionIdentify essential scientific reasoning steps and computational outputsDevelop grading logic capable of distinguishing correct solutions from plausible but flawed approachesEnsure evaluation standards remain precise and reproducibleTesting & Difficulty CalibrationTest tasks against advanced computational systemsAnalyse common scientific, numerical, and reasoning failure modesRefine prompts, inputs, constraints, and expected outputs based on testingAdjust difficulty while preserving scientific validityFinalise tasks only when they reliably require advanced materials science expertiseResearch Engineering WorkflowWork through a Git/GitHub pull-request workflowRun and validate code within Docker-based environmentsRespond to automated quality checks and reviewer feedbackMaintain clean, reproducible code and supporting documentationCollaborate effectively within structured scientific software workflowsIdeal ProfilePhD required in Materials Science, Materials Engineering, Applied Physics, Chemistry, Chemical Engineering, or a closely related fieldDemonstrated expertise in both semiconductor materials and molecular modelingStrong working proficiency in Python, R, or another scientific programming languageHands-on experience using scientific code for materials modelling, simulation, numerical analysis, or computational researchComfortable with Git/GitHubExperience running code in Docker or other containerised environmentsStrong understanding of reproducible scientific computingAbility to translate advanced materials research into clearly defined computational problemsPeer-reviewed publications are highly valuedPrior scientific software or research engineering experience is advantageousStrong written communication and ability to document scientific assumptions, methods, and solutions preciselyEngagement DetailsPart-time independent contractor engagementFully remote20+ hours per weekInitial duration of approximately 6 weeksImmediate startCompensation: Up to $60/hourWork includes materials science problem design, scientific coding, reference-solution development, grading criteria, testing, and task refinementProjects may be extended, shortened, or concluded based on project needs and performanceWork must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third partyH1-B and STEM OPT support is unavailable for this engagementThis opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy.