Summary
Somayeh Faraji is a researcher and data analyst with nine years of experience applying density functional theory, machine learning, and computational modeling to materials and nanophysics problems. She has held postdoctoral roles across Europe and the U.S., including work on 2D materials discovery using DFT and genetic algorithms and on high-pressure thermal conductivity using ML-accelerated simulations. Comfortable in Python, Unix/HPC environments, and neural-network approaches, she bridges theoretical physics and data-driven materials discovery. Based in Gainesville, Florida, she is seeking research positions that offer technical growth and interdisciplinary collaboration, bringing both academic rigor and practical coding experience to computational materials problems.
9 years of coding experience
3 years of employment as a software developer
Doctoral Researcher, Nanophysics and computational condensed matter, Doctoral Researcher, Nanophysics and computational condensed matter at Institute for advanced studies in basic sciences
Master of Science (MSc), Condensed Matter and Materials Physics, Master of Science (MSc), Condensed Matter and Materials Physics at Shahrekord University
Persian, English, German