{"id":916285,"url":"https://alion.io/job/weekday-material-science-phd-coding-experts","title":"Material Science PhD Coding Experts","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":92,"ghost_share":0,"stale_share":0.967,"repost_share":0,"time_to_fill_p50_days":5,"computed_at":"2026-10-07T05:47:15Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":70,"max":null,"currency":"USD","period":"hour","gross":null,"usd_annual":140000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Python","optional":false},{"name":"Stripe","optional":false}],"status":"live","first_seen_at":"2026-09-14T00:00:00Z","employer_posted_date":"2026-09-14","last_verified_at":"2026-10-07T23:42:33Z","board_verified":true,"closed_at":null,"days_open":24,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":24},"description":"This role is for one of our clients\nCompensation: $70 per hour\nWe are hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code)\nMercor is partnering with leading AI labs on a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.\nDomains - depth required in at least two subdomains (with a coding focus)\nMaterials science - semiconductor materials, molecular modeling\nRequirements\nWhat you'll do\nSource your own material: a published paper, a Kaggle dataset, an open-source repository, or a scenario you design\nWrite scientific prompts based on the input\nBuild the grading criteria that define a correct answer\nCalibrate against frontier models - a task ships only when strong models fail it more often than they succeed\nRequired\nPhD in materials science, materials engineering, applied physics, chemistry, chemical engineering, or a closely related field\nDemonstrated depth in both of the following subdomains: semiconductor materials and molecular modeling\nWorking proficiency in Python, R, or another relevant programming language for scientific computing\nComfortable with Git/GitHub and running code in Docker - authoring runs through a pull-request workflow with automated quality checks\nPreferred\nPublications in peer-reviewed journals\nPrior scientific software or research engineering experience\nEngagement\nDuration: 6 weeks\nCommitment: part-time, 20+ hours per week\nStart date: immediate\nProcess\nUpload your resume and application form\nA 25-minute conversational interview covering your background, experience, and motivations\nFollow up within a few days with next steps and onboarding\nApply today and put your research expertise to work building the next generation of scientific AI.\nWe consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.\nContract and Payment Terms\nYou will be engaged as an independent contractor.\nThis is a fully remote role that can be completed on your own schedule.\nProjects can be extended, shortened, or concluded early depending on needs and performance.\nYour work will not 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