Stage per Tesi Magistrale
Pubblicato il 15-08-2026 - STEVANATO GROUP in Piombino Dese
Job Description
This Master’s Thesis offers the opportunity to work on a high-impact engineering project at the intersection of pharmaceutical manufacturing, heat transfer, and computational modelling. The selected candidate will contribute to the development of a multiscale numerical workflow designed to predict the thermal history of pharmaceutical glass containers moving through depyrogenation tunnels, a critical process step in aseptic manufacturing.
Job Description
This Master’s Thesis offers the opportunity to work on a high-impact engineering project at the intersection of pharmaceutical manufacturing, heat transfer, and computational modelling. The selected candidate will contribute to the development of a multiscale numerical workflow designed to predict the thermal history of pharmaceutical glass containers moving through depyrogenation tunnels, a critical process step in aseptic manufacturing.
This project is part of a broader industrial digital twin initiative aimed at extending thermal assessment beyond standard qualification scenarios.
It offers the chance to apply advanced simulation methods to a real industrial challenge, supporting process understanding, validation, and future digitalization efforts in a highly regulated environment.
Main Activities
- Analyse available qualification and experimental data related to depyrogenation tunnel performance;
- Extract and structure boundary conditions for thermal and flow simulations;
- Develop Python-based tools, including a vial-array pre-processor and supporting numerical utilities;
- Implement and use thermal solvers to estimate vial temperature evolution;
- Perform micro-scale CFD simulations to derive heat-transfer inputs for the larger model;
- Support macro-scale CFD simulations of the depyrogenation tunnel environment;
- Compare model predictions with an available experimental case for preliminary validation.
Qualifications
We are looking for an MSc student with a structured and analytical min