AM LPBF Simulation Lab Intern – Master’s Thesis

Leonardo; Varese; Hybrid; EUR 8,900 - 12,000; Full time

Benefits offered by this job

Hybrid working arrangement

Monthly stipend €800

Job summary

Leonardo seeks a Master’s thesis intern for the Technology Lab & Inspection team in Cascina Costa (VA). You will develop and validate LPBF models, predicting temperature, residual stresses, and distortions, supporting AM advancement for aerospace.

The role blends research and industrial application within a multidisciplinary environment. The project focuses on digital engineering for AM, with deliverables including model development, validation against data, and a thesis documenting

Qualifications

• Solid analytical and problem-solving capabilities.
• Fundamental knowledge of heat transfer, solid mechanics, and numerical methods.
• Basic understanding of Finite Element Analysis (FEA).
• Strong interest in AM and Materials Engineering.
• Ability to work effectively in a team and in a structured engineering environment.

Responsibilities

• Review the state-of-the-art in AM process simulation.
• Definition and implementation of finite element or numerical models for LPBF processes.
• Application of appropriate material models and boundary conditions.
• Execution of simulation campaigns.
• Analysis and interpretation of outputs (thermal fields, stress distribution, distortion).
• Correlation with experimental evidence where available.
• Contribution to internal best practices and methodological guidelines.

Skills

Analytical thinking

Heat transfer

Solid mechanics

Numerical methods

Familiar with teamwork

English proficiency

Education

Ongoing Master’s Degree in Mechanical, Materials or Aeronautical Engineering

Background in Materials Science, Manufacturing Processes, or Structural/Mechanical Analysis

Tools

Abaqus

Ansys

Simufact Additive

Python

MATLAB

Job description

Leonardo seeks a Master’s thesis intern for the Technology Lab & Inspection team in Cascina Costa (VA). You will develop and validate LPBF models, predicting temperature, residual stresses, and distortions, supporting AM advancement for aerospace.

The role blends research and industrial application within a multidisciplinary environment. The project focuses on digital engineering for AM, with deliverables including model development, validation against data, and a thesis documenting