Doktorand inom Teoretisk Fysik
Core
Research on first-principles modeling of point defects in semiconductor materials, focusing on realistic and complex environments including alloys, disordered, and finite-temperature systems.
Role type
PhD researcher (theoretical physics)
Builds
Production ML models | research
Domain
Condensed matter physics, computational physics, machine learning
Deliverable
research
Required skills
First-principles methods for electronic structure, defect physics in semiconductors, machine learning applied to physical systems, quantum mechanics, statistical physics, computational physics
Preferred skills
Thermodynamics, programming, scientific calculations, high-performance computing (HPC), Python, Fortran, C/C++
Technologies
Python, Fortran, C/C++, HPC
Responsibilities
Conduct research on first-principles modeling of point defects in semiconductor materials, apply quantum mechanical and machine learning-based methods, teach or participate in other institutional duties up to 20% of full-time
Seniority
PhD level, research-focused