Master Thesis – From Process Parameter Recipes to Process Intent in LPBF

Location: Finspång, Östergötland County, Sweden

Company

hirify.global develops energy technologies and provides service, modernization, decarbonization, and digitalization solutions for power-generation systems.

What you will do

• Analyze historical LPBF manufacturing data to understand the complexity and engineering effort of recipe-based manufacturing.
• Develop a feature-based description of the manufacturing process using geometry, material, thermal history, build position, and neighboring-part interaction.
• Use Optical Tomography, monitoring data, process settings, and geometry information to predict density, porosity, dimensional accuracy, distortion, and surface quality.
• Develop and evaluate an intent-based recommendation concept that translates quality and productivity requirements into manufacturing actions and process settings.
• Test the approach with a new geometry or material and investigate first-time-right manufacturing without developing a new parameter recipe.
• Work collaboratively with specialists across design, materials, manufacturing, process development, and digitalization while independently driving the thesis.

Requirements

• Currently studying toward a Master's degree in Mechanical Engineering, Additive Manufacturing, Materials Engineering, Production Engineering, Applied Physics, Data Science, Machine Learning, or a related field.
• Curiosity about the intersection of physical manufacturing processes, engineering, and data-driven methods, with an interest in solving problems with real industrial relevance.
• An analytical mindset and comfort working with complex datasets.
• Ability to structure an open research question into testable hypotheses and translate results into practical engineering solutions.
• Ability to work collaboratively with specialists from different technical disciplines and independently conduct thesis work.

Nice to have

• Experience with Python, MATLAB, or similar data-analysis tools.
• Knowledge of LPBF or additive manufacturing, process monitoring, machine learning, digital twins, or manufacturing simulation.

Culture & Benefits

• Work in an Additive Manufacturing environment connected to Beacon Build, Optical Tomography fingerprinting, OT Predictive, digital twins, Smart Fusion, automated qualification, and adaptive LPBF initiatives.
• Collaborate with experienced additive-manufacturing specialists on a research question with direct industrial relevance.
• Employment benefits include reduced working hours, advance vacation, and a health care allowance.
• Possibility of a flexible workplace may become available.
• Inclusive environment with colleagues from more than 90 countries and over 130 nationalities.

Hiring process

• Apply by 17 November 2026; ongoing selection applies and the role may be filled earlier.