Nicholas Noll

Background

About Nicholas Noll

I am a Physicist working in the broad domain of Quantitative Biology. As a field, Biology has entered an exciting new era of rapid technological advancement and, thus, large heterogeneous datasets that provide us with an unprecedented, quantitative view of living systems. However, it remains challenging to synthesize such disparate data into interpretable, predictive models. My work is focused on contributing to the advancement of modeling biological systems, which in the past has contributed to the understanding of the morphogenesis of early development, epidemiology, and bacterial evolution. I have a demonstrated history of working in scientific research in primarily computational and analytical roles. All my projects have resulted in two major outputs, a simple physically-motivated model that informs the core of an algorithm encapsulated by an open-sourced command-line interface. I am highly proficient in many programming language, including but not limited to: Julia, Python, MATLAB, Go and C. My Github page, github.com/nnoll, is a representative cross-section of my work. As I have worked on a wide array of problems within Biology, I have intimate, hands-on experience wrangling data from many technologies at the forefront of biology. These include: an image-analysis pipeline that can segment epithelial tissues from confocal/SPIM live-image datasets; a hybrid ONT/Illumina assembly pipeline used in collaboration with clinical collaborators; a pan-genome alignment tool; a scRNAseq analysis toolkit used on raw reads to learn low-dimensional latent representations of developing systems using a novel machine learning approach; and an open epidemiological modeling framework used for hospitals during the beginning of the COVID-19 pandemic. I am very interested in any work that applies the advancements from computational/quantitative biology to medicine and the nascent field of individualized therapeutics.