Intern

Description du poste:

About the Opportunity
We are looking for four highly motivated Chemical Engineering interns from premier institutes (IITs/NITs) to work on cutting-edge projects in process modelling, simulation, and data science.
This internship will focus on integrating mechanistic modelling (CFD, DEM) with modern data-driven approaches (AI/ML) to solve complex engineering problems in fluid and particulate systems.
Key Responsibilities
* Develop and apply Computational Fluid Dynamics (CFD) models for fluid flow, heat, and mass transfer
* Build and analyze Discrete Element Method (DEM) models for particle and powder systems
* Create and modify CAD geometries for simulation workflows
* Write efficient Python scripts for data analysis, model automation, and visualization
* Apply machine learning and AI techniques for predictive modelling and optimization
* Integrate physics-based models with data-driven approaches
* Analyze results and generate actionable insights
* Collaborate with cross-functional teams and present findings
Eligibility Criteria
* Pursuing B.Tech in Chemical or Mechanical Engineering
* From IITs, NITs, or equivalent premier institutes
* Strong foundation in:
* Transport phenomena
* Mechanical operations
Desired Skills
* Exposure to one or more of the following:
* CFD tools: ANSYS Fluent, OpenFOAM, COMSOL
* DEM tools: EDEM, LIGGGHTS, Rocky
* CAD software: SolidWorks, AutoCAD
* Strong programming skills in Python (NumPy, pandas, matplotlib, etc.)
* Basic understanding of machine learning / AI concepts
* Strong analytical and problem-solving capability
What You Will Gain
* Hands-on experience with CFD, DEM, and CAD tools
* Exposure to AI/ML applications in engineering workflows
* Opportunity to work on industry-relevant, high-impact projects
* Mentorship from experienced scientists and engineers
* Potential pathway to full-time opportunities

Work Location Assignment: Hybrid

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

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