Experience Data C++ Functional Work University

Michael A. Grosner

** ***** ** *** *********, NJ 08901

www.michaelgrosner.com **************@*****.***

716-***-****

Objective

To obtain entry-level employment in the nancial industry using my quantitative and computational skills.

Education

Rutgers University, Ph.D. Candidate in Computational Biophysics August 2010 - Present

Relevant Coursework : Numerical Analysis, Computational Physics, Chemical Dynamics, Biophysics

Current GPA: 3.7

Fordham University, B.S. in Physics August 2005 - May 2009

Relevant Coursework : Statistical Physics, 4 courses on mathematical methods in physics covering

linear algebra and di erential equations, Computational Physics

Physics GPA: 3.9

Research

Monte Carlo Simulation of DNA, Rutgers University March 2011 - Present

Currently working with Dr. Wilma Olson of the Chemistry Department to investigate the dynamics

and structure of protein-bound DNA. We employ coarse-grained, physics-based models of DNA using

Metropolis Monte Carlo and Gaussian Sampling simulation in C++.

Also interested in creating MySQL/SQLite databases of structural information to preform data mining.

Publication : Con rmation for Interplay of Protein and DNA Structure Revealed in Simulations of the

lac Operon, PLoS One, Submitted Aug 8, 2012.

Stochastic Biology, Fordham University January 2008 - March 2009

Assisted Dr. Kunal Das of the Physics Department on researching stochastic, nonlinear and critical

processes in economics and cell biology.

Worked on a Runge-Kutta ODE solver and implemented a numerical, multidimensional shortest-path

algorithm using Monte Carlo methods in Fortran 90.

Computer Skills

Programming Languages : Python, C, C++, bash/zsh, JavaScript, MATLAB, and Fortran 90

Tools : Git, MySQL/SQLite, Eclipse CDT, NumPy/SciPy, Eigen, Boost, OpenMP, and Django

Work Experience

Amgen Inc., Computational Chemistry Graduate Summer Intern June 2012 - August 2012

Developed a novel data mining algorithm to identify matched molecular pairs (a pair of small, drug-like

compounds which by a single functional group) in large datasets in near-linear time.

Used this algorithm and regression analysis to identify functional groups which may activate proteins

involved in detoxi cation.

Implemented the algorithm in Python and C++, performed statistical analysis in Python.

Awards and Conferences

GAANN Fellowship Spring 2012 - Present

Attended PyCon 2012 in Santa Clara, CA March 2012

Rutgers University Excellence Fellowship 2010-2011

Fordham Dean s O ce Summer Science Internship Summer 2008

Presented poster at APS/AAPT Joint Spring Topical Symposium at Cornell University April 2008

Citizenship Status : Full US Citizen

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