Emel Ficici

Emel Ficici

Postdoctoral Irta Fellow @ National Institutes of Health

About Emel Ficici

Emel Ficici is a Postdoctoral Irta Fellow at the National Institutes of Health, specializing in molecular dynamics simulations and free energy calculations. With a strong background in physics and chemistry, she has held various academic positions and possesses advanced programming skills in Python.

Current Position at National Institutes of Health

Emel Ficici has been serving as a Postdoctoral Irta Fellow at the National Institutes of Health since 2015. In this role, she engages in advanced research focusing on physical chemistry, specifically utilizing molecular dynamics simulations. Her work contributes to understanding biomolecular interactions and the development of artificial molecules.

Previous Experience at Uc Irvine

Prior to her current position, Emel Ficici worked at the University of California, Irvine as a Graduate Student Researcher and Teaching Assistant from 2010 to 2015. During this five-year tenure, she gained extensive experience in research methodologies and teaching, enhancing her expertise in physics and chemistry.

Teaching Role at Spring Hill College

Emel Ficici served as an Adjunct Lecturer at Spring Hill College for one year, from 2005 to 2006. This position allowed her to share her knowledge in physics with undergraduate students in Mobile, Alabama, contributing to their academic development.

Educational Background

Emel Ficici holds a Bachelor of Science in Teaching and Physics from Boğaziçi University, which she completed from 1992 to 1997. She furthered her education by obtaining a Master of Science in Physics from Orta Doğu Teknik Üniversitesi between 1997 and 1999. She completed her Doctor of Philosophy in Physics, Chemistry, and Philosophy at the University of California, Irvine from 2010 to 2015.

Research Skills and Techniques

Emel Ficici specializes in molecular dynamics simulations, focusing on both biomolecules and artificial molecules. She employs advanced techniques such as Free Energy Perturbation Method, Umbrella Sampling, and Adaptive Biasing Force Method for Free Energy Calculations. Her programming skills in Python enhance her research capabilities in physical chemistry.

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