Forskare i modellering för materialdesign
Core
Develop and apply physics-informed machine learning methods for steel design, specifically linking composition, processing, microstructure, and properties to support new alloy development.
Role type
Researcher in modeling for material design (PhD level)
Builds
Physics-informed models for heat treatment of steel
Domain
Materials science + Machine learning
Deliverable
production ML models
Required skills
Physics-informed machine learning, thermodynamics, computational materials science, Python programming, experimental data validation
Preferred skills
Method development integrating physics-based approaches with data-driven methods and experiments, recent PhD in computational materials science
Technologies
Python
Responsibilities
Develop physics-informed models for steel heat treatment, collaborate with industrial partners, validate models using experimental data, support development of sustainable steel production processes
Seniority
Senior, hands-on IC