Computational Physicist
Resume:
D. Jeffrey Fraser
*** *. ****** ****, ************, PA
******@*****.***
PROFILE
Skilled analyst with sophisticated model creation and validation experience in computational biophysics. Strong background in mathematics and programming. Highly adept at learning new concepts quickly,
working well in teams and under pressure, and communicating ideas clearly and effectively.
EDUCATION
THE PENNSYLVANIA STATE UNIVERSITY,
State College, Pennsylvania
PhD, Physics 2009
Dissertation focused on computational neural network models
YORK UNIVERSITY, Toronto, Ontario, Canada
B.Sc Honours, Physics and Astronomy 2003
COMPUTER SKILLS
Programming
C++, BASH, Fortran 77
Software
Matlab, Maple, Microsoft Word, Excel, Power Point
Operating Systems
Linux (Redhat, openSUSE), Windows XP
RESEARCH EXPERIENCE
The Pennsylvania State University 2005 – 2009
Dissertation focused on computational neural network models under advisor Dezhe Jin
• Reduced a highly complex motor system of animals into a simplified dynamic neural network capable of
reproducing the observed learning of song in developing zebra finch songbirds.
• Reproduced complex neuron properties using a set of nonlinear partial differential equations (Hodgkin
Huxley Equations) evolved in C++.
• Teaching duties included supervision and instruction of theoretical and laboratory exercises. Also helped
to revise course structure and content.
Relevant Courses:
Mathematical Methods
Statistical Mechanics (Calculus of Variations)
Computational Neuroscience
General Relativity (Differential Geometry)
Computational Physics (in JAVA)
Critical Phenomenon (Mean Field Theory)
York University 1999 – 2003
• Performed Mass Spectrometry at the DESY Particle Accelerator in Hamburg, Germany. Research involved learning new syntax to communicate with servers requesting data runs from actual experiment. Programming was done in Fortran 77 and BASH environment.
• Evolved nonlinear differential equations of a quantum mechanical system in a Maple environment.
Relevant Courses:
Linear Algebra Complex Variables I & II
Numerical Methods I & II
Partial Differential Equations
Computational Physics (in MAPLE)
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