Michael G. Lerner

Associate Professor
Earlham College
Department of Physics and Astronomy


I study membranes, computational oncology, nucleic acids, proteins and dynamics. I spend my time developing the physics-based methods required to understand the interplay between the four so that we can adress fundamental biological questions relating to drug design, intracellular interactions, and a host of related problems. I am a computational biophysicist, and my work includes molecular dynamics simulations, computational methods design, and the development of purely analytical models ranging from differential equations to computational topology. I've even been known to enjoy lab work including both single molecule studies on nucleic acids and scanned probe microscopy on biochemical systems.

I'm interested in broader health impacts, and I'm currently spending a sabbatical at Johns Hopkins, applying my background in computational statistical mechanics, software design, and data analysis to reduce the suffering and death caused by cancer

I use and develop open-source packages whenever I can, leaning towards PyMOL and Python in particular. I use CHARMM, AMBER, and GROMACS for my simulations and write a lot of Python code for analysis. I wrote and maintain the PyMOL-APBS plugin as well as PyPAT. Recently, I've been putting my code up on github.

I also have a strong passion for teaching and a diverse teaching background including everything from spending a year working for City Year in an inner-city Chicago public school, to mentoring undergraduate and graduate students, to teaching calculus-based E&M labs and lectures for the Univeristy of Michigan's physics department, to my current job teaching in the Department of Physics and Astronomy at Earlham College.

Every year in my introductory classes, students do independent projects to push back at the false narrative that physics has been performed entirely by people who look like Isaac Newton. This resulted in a set of freely-available, automatically-generated slides, tied to the relevant sections of popular introductory texts, and organized so that any instructor can easily incorporate more inclusive information in their own courses. Are you interested in physics? Please feel free to contribute!. Do you teach physics? Please use these materials! I'd love to help incorporate them into your classes!

In addition to winning the yearly prize for best Graduate Student Instructor in the Physics department, I was selected as a Michigan Teaching Fellow by the Center for Research on Learning and Teaching. I developed and taught a one-day hands-on introduction to scientific data analysis with open source tools including Python and matplotlib for wet-lab biologists with little to no programming experience. Most recently, I've taught calculus-based introductory physics with lab, mathematical and theoretical physics, computational science, statistical thermal physics (you can play along with our Monte Carlo modeling of March Madness brackets this year by downloading the code we wrote!), classical electricity and magnetism, and a senior seminar in advanced statistical mechanics and computer simulation.

I'm an Associate Professor in Earlham College's Department of Physics and Astronomy. I was an NIH IRTA Postdoctoral Fellow in the NHLBI's Laboratory of Computational Biology with Rich Pastor and Bernie Brooks. I did my graduate work with Heather Carlson at the University of Michigan and my undergraduate work with Walter Smith at Haverford.