MolSSI Software Fellow Alum: Dr. Josh Rackers
Dr. Josh Rackers, one of our MolSSI Software Fellow alums, is currently a Harry S. Truman Fellow at Sandia National Laboratories in New Mexico. Josh, who was a 2018 Phase I Fellow, received his PhD from Washington University in St. Louis under the direction of Prof. Jay W. Ponder. While a MSF he worked on making HIPPO, the next generation of the AMOEBA force field, more accurate and more widely available.
How did you first become interested in molecular science?
Teaching high school physics. My students challenged me to think about ways physics matters to the real world. I’m not sure why, but the idea of using physics to understand how biological molecules work got lodged in my head.
How did you benefit from being a MolSSI Software Fellow?
The chance to meet other fellows was great. Hearing about what other folks are doing has always helped me conceptualize what I think is important in science. Having that in person experience was a great opportunity to engage with ideas outside of my own scientific bubble.
Describe your engagement with your MolSSI Software Scientist mentors.
Both Drs. Daniel G. Smith and Eliseo Marin-Rimoldi helped, but in different ways. Eliseo helped set out a list of priorities for the project. Daniel contributed concrete building blocks of code.
What are your long-term career plans?
I would like to run a research group and teach as a professor.
Do you have any skills or talents that most people would not know about?
I’m a sourdough bread baker! Although now in the pandemic, apparently I’m not alone!
What accomplishment are you most proud of?
Creating an entirely new molecular mechanics model, HIPPO, starting basically from pencil-and-paper theory.
What are you happiest doing when you’re not working?
Being outside. Life here in New Mexico is incomparable when it comes to the outdoors. The family and I are out hiking, camping, biking and skiing as often as we can.
What’s a goal you have for yourself that you’d like to accomplish in the next year or two?
Test the machine learning project I’ve been building on a protein.
Message from Josh to readers:
If you’re interested in the Grand Challenge of how to simulate biological molecules from first principles, I want to be your friend! Whether we work together, collaborate or just share ideas, I am a firm believer that science is best done as a shared endeavor. So shoot me an email — I’d love to hear your big ideas for how we should be tackling this problem!