{"id":3838851,"url":"https://alion.io/job/astrazeneca-manufacturing-digital-and-ai-intern","title":"Manufacturing Digital and AI Intern","company":{"id":13195,"name":"AstraZeneca","domain":"astrazeneca.com","url":"https://alion.io/company/astra-zeneca","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":94,"open_postings":171,"ghost_share":0.006,"stale_share":0.374,"repost_share":0.099,"time_to_fill_p50_days":19,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gaithersburg, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":37,"max":39,"currency":"USD","period":"hour","gross":null,"usd_annual":78000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Digital Twin","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Computer Vision","optional":true}],"status":"live","first_seen_at":"2026-11-05T21:57:24Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-06T13:47:21Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for rising sophomores, juniors, and seniors studying Computer Science, Biomedical Engineering, Chemical Engineering or a related field for a 12-week internship role at our site in Gaithersburg, MD from May 24, 2027 to August 13, 2027.\nPosition Description:\nAnalyze clinical manufacturing process data and develop Python-based prototypes for predictive analytics, anomaly detection, and decision support to improve operational efficiency and process understanding. \nSupport digital manufacturing projects, including electronic batch records, digital supply chain, digital technology transfer, and digital twins, by mapping processes, equipment, data sources, and interfaces to define data requirements and integration needs. \nAssess robotics and intelligent automation opportunities, such as automated material handling, robotic sampling, machine vision, and laboratory automation, by developing use cases and conducting technology assessments and feasibility studies. \nCollaborate with manufacturing, engineering, automation, data science, and digital technology teams to identify high-value digital opportunities and develop business cases, requirements, and implementation roadmaps.\nPosition Requirements:\nRising sophomores, juniors, and seniors studying Computer Science, Biomedical Engineering, Chemical Engineering or a related field.\nIntroductory exposure to machine learning, generative AI, or large language models through classes or small projects is preferred.\nBasic Python programming skills and experience analyzing or visualizing data through coursework, academic research, or personal projects are beneficial.\nFamiliarity with tools such as Pandas, NumPy, scikit-learn, SQL, or Power BI is a plus.\nCoursework or project experience involving digital twins, process simulation, robotics, computer vision, or industrial automation is a plus.\nAn interest in biopharmaceutical manufacturing and a willingness to learn how digital technologies support manufacturing operations are beneficial.\nExperience collaborating on student projects, researching technical topics, and clearly presenting findings is beneficial.\nCandidates must have an expected graduation date after August 2027.\nUS Work Authorization is required at time of application.\nThis role will not be granting CPT support.\nAbility to report onsite to Gaithersburg, MD site 5 days per week. 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