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<!DOCTYPE HTML>
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<h1><a href="index.html">Marc Descoteaux</a></h1>
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<h2>Research</h2>
<p>I work in computational materials science and chemistry leveraging new techniques in machine learning to understand and predict the behavior of molecular systems accurately and efficiently.</p>
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<h3 class="major">Materials Intelligence Research</h3> <h4 style="font-weight:lighter; display:inline">September 2023 — Present</h4>
<p>With <a href="https://mir.g.harvard.edu/" target="_blank" rel="noopener noreferrer"> Prof. Boris Kozinsky in Harvard Engineering
</a>, I use machine learning and molecular dynamics simulation to acquire atomistic insights into materials and molecules.</p>
<h3 class="major">The YSL Lab</h3> <h4 style="font-weight:lighter; display:inline">January 2021 — August 2023</h4>
<p>With <a href="https://sites.tufts.edu/ysllab/" target="_blank" rel="noopener noreferrer"> Prof. Yu-Shan Lin in Tufts Chemistry
</a>, I used molecular dynamics with enhanced sampling to understand the relationships between sequence and structure in cyclic peptides.</p>
<p>To push the boundaries of high throughput structural analysis, the lab uses machine learning to learn the structural ensemble of cyclic peptides observed in MD so that we can replace the need to perform MD after training an ML model (
<a href="https://pubs.acs.org/doi/10.1021/acs.jctc.3c00154" target="_blank" rel="noopener noreferrer">
<em>
J. Chem. Theory Comput.
</em>
<b2>
2023
</b2>
</a>,
<a href="https://pubs.rsc.org/en/content/articlehtml/2021/sc/d1sc05562c" target="_blank" rel="noopener noreferrer">
<em>
Chem. Sci.
</em>
<b2>
2021
</b2>
</a>
). These models represent a multiple order-of-magnitude speedup in the calculation of a cyclic peptide's structural ensemble.
With this technology, we can begin to enable structure-based <i>de novo </i> cyclic peptide drug design.</p>
<h3 class="major">The Staii Lab</h3> <h4 style="font-weight:lighter; display:inline">May 2020 — December 2020</h4>
<p>With <a href="https://as.tufts.edu/physics/people/faculty/cristian-staii" target="_blank" rel="noopener noreferrer"> Prof. Cristian Staii in Tufts Physics and Astronomy</a>, I developed
theoretical models to explain why neuron axons tend to align themselves with and grow along periodic patterns in their substrate
( <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257659" target="_blank" rel="noopener noreferrer">
<em> PLOS One. </em>
<b2>2021</b2>
</a>,
<a href="https://www.sciencedirect.com/science/article/pii/S0006349522000704" target="_blank" rel="noopener noreferrer">
<em> Biophys. J. </em>
<b2>2022</b2></a>). I also helped show that
the dielectric properties of nanoparticles can be measured with electrostatic force microscopy (EFM) (
<a href="https://aip.scitation.org/doi/full/10.1063/5.0028132" target="_blank" rel="noopener noreferrer">
<em> AIP Adv. </em>
<b2>2020</b2>
</a>).
</p>
<h3 class="major">The Kaplan Lab</h3> <h4 style="font-weight:lighter; display:inline">May 2019 — March 2020</h4>
<p>With <a href="https://sites.google.com/view/supranano/home?authuser=1" target="_blank" rel="noopener noreferrer"> Dr. Jugal Sahoo </a> in <a href="https://engineering.tufts.edu/bme/kaplan" target="_blank" rel="noopener noreferrer"> Prof. David Kaplan's lab in Tufts Biomedical Engineering </a>,
I worked to create silk-fibroin-based hydrogels and understand how their physical and chemical properties and biocompatibility changed
when prepared with different methods (
<a href="https://pubs.rsc.org/en/content/articlelanding/2020/bm/d0bm00512f/unauth" target="_blank" rel="noopener noreferrer">
<em> Biomater. Sci. </em><b2>2020</b2></a>
) and functionalized with different sugars (
<a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adbi.202100388" target="_blank" rel="noopener noreferrer">
<em> Adv. Biol. </em>
<b2>2021</b2>
</a>
).
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<h2 class="major">Find me elsewhere</h2>
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