Intern Job Description – Global Technology Engineering and Launch-Analytical technology (GTEL-AT)
Role Summary
Join our Global Technology Engineering and Launch-Analytical technology (GTEL-AT) team as an intern focused on advancing digital transformation in Analytical Technology. You will develop computational tools and system-level models to support process characterization and optimization, with an emphasis on hybrid modeling (data-driven + mechanistic), process monitoring/control, and automation projects aligned with the Lab of the Future (LoTF) vision. Your talent will be tapped for digital fluency enhancement of the colleagues.
Key Responsibilities
-
Digital Fluency Training: Provide training sessions to colleagues to enhance digital fluency and adoption of AI tools and analytics within the department.
-
Vendor Collaboration: Engage with external vendors to co-develop AI-based digital application tailored for Analytical Technology workflows.
-
Project Support: Work collaboratively with cross-functional teams to run automation projects, contributing to the development of the Lab of the Future (LoTF).
-
Model Development: Develop and validate a model for TRS100 in partnership with departmental subject matter experts (SMEs) and vendors.
-
Computational Modeling: Apply data-driven modeling, machine learning, AI, statistical methods, and mechanistic models to process development and monitoring.
-
Chemistry & Analytics: Utilize a strong foundation in basic chemistry and analytical techniques to support project objectives and ensure scientific rigor.
-
Results Communication: Present findings and progress to internal teams and, occasionally, at external forums, using data analysis and visualization tools.
Basic Qualifications
-
Undergraduate or postgraduate student in Chemical Engineering, Biochemical Engineering, Mechanical Engineering, Process Control Engineering, Pharmaceutical Engineering, Biotechnology, Chemistry, Analytics, or related discipline.
-
Academic focus on data-driven or mechanistic modeling, with demonstrated experience in computational techniques.
-
Strong background in basic chemistry and analytics.
-
Experience with programming (Python, R, MATLAB, C/C++), numerical methods, and high-performance computing (Linux-based environments).
-
Excellent organizational and interpersonal skills; able to manage multiple projects and work effectively in cross-functional teams.
-
Strong written and verbal communication skills.
Preferred Qualifications
-
Experience in modeling and developing digital applications for laboratory environments.
-
Prior involvement in automation or digital transformation projects in laboratory or manufacturing settings.
Work Location
Work Location Assignment: On Premise
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Support Services
