{"id":1252572,"url":"https://alion.io/job/astar-ai-scientist-composite-materials-imre","title":"AI Scientist, Composite Materials, IMRE","company":{"id":50235,"name":"Agency for Science, Technology and Research","domain":"a-star.edu.sg","url":"https://alion.io/company/a-star-edu","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"B","score":81,"open_postings":47,"ghost_share":0,"stale_share":0.979,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":49000,"max_usd":133000,"period":"year","method":"role_country_seniority_unknown","sample_n":112},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Matplotlib","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"SciPy","optional":false},{"name":"Git","optional":true},{"name":"Linux","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-09-25T18:36:13Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-10-24T05:55:21Z","board_verified":true,"closed_at":null,"days_open":28,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":28},"description":"Long Description\nJob Description\nWe are seeking a highly motivated Research Scientist to join our interdisciplinary team developing next-generation AI-driven materials discovery platforms. The successful candidate will contribute to the integration of experimental materials research, scientific data infrastructure, and artificial intelligence to accelerate the discovery and optimization of advanced materials.\nThis role offers the opportunity to work closely with experimental scientists, computational researchers, and AI specialists to develop data-driven workflows that enable autonomous materials research. The candidate will contribute to projects spanning materials synthesis and characterization, scientific data management, machine learning, and laboratory workflow automation. Opportunities for scientific publications, intellectual property development, industrial collaborations, and technology translation are also available.\nKey Responsibilities\nDesign, conduct, and support experimental research on advanced materials, including synthesis, processing and characterization.\nDevelop standardized automated experimental protocols and ensure high-quality, reproducible scientific data generation.\nBuild, curate, and maintain high-quality materials datasets from experimental, computational, and literature sources.\nDevelop automated data processing and analysis workflows to support AI-driven materials discovery.\nDevelop Python-based tools and scientific workflows for data collection, preprocessing, visualization, and analysis.\nCollaborate with researchers to integrate laboratory instruments, databases, and computational workflows into a unified research platform.\nApply machine learning, statistical analysis, and data-driven approaches to identify structure-property-processing relationships and accelerate materials optimization.\nSupport the development of AI-assisted research tools, including scientific databases, knowledge management systems, and autonomous experimentation workflows.\nWork collaboratively with multidisciplinary teams across materials science, chemistry, computer science, automation, and data science.\nRequirements\nPhD in Materials Science and Engineering, Chemistry, Chemical Engineering, Computational Materials Science, Computer Science, Electrical Engineering or a related discipline.\nExperience with experimental techniques relevant to advanced materials research.\nProgramming experience in Python for scientific computing, data analysis, or workflow development.\nFamiliarity with scientific programming libraries such as PyTorch, NumPy, pandas, SciPy, matplotlib, or similar.\nExperience developing data analysis pipelines, automation scripts, or scientific software is advantageous.\nExposure to machine learning, artificial intelligence, data science, or materials informatics is highly desirable.\nFamiliarity with SQL, databases, data management, version control (Git), Linux, or high-performance computing environments is advantageous.\nStrong analytical and problem-solving skills with the ability to work independently and collaboratively.\nDemonstrated ability to contribute to multidisciplinary research projects.","description_format":"text","description_chars":3166,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Advanced Materials","Materials Science & Nanotechnology"],"lifecycle":[{"event":"open","at":"2026-09-25T18:36:13Z"}],"visa":[],"liveness":{"score":20,"band":"cold","label":"Long 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