Hamish Swanson, Ph.D.

Hamish Swanson is a postdoctoral researcher at the Advanced Science Research Center at the CUNY Graduate Center in the group of Professor Rein Ulijn. He received his M.Chem. degree in pure and applied chemistry at Strathclyde University, Glasgow and completed his Ph.D. in 2024 under the joint mentorship of Professor Tell Tuttle and Dr Aaron Lau. He secured scholarship funding from the Carnegie Trust for the Universities of Scotland for his Ph.D. During his time at Strathclyde, Hamish was awarded both the Professor DC Sherrington FRS postgraduate prize for his Ph.D. thesis and the Sir George Beilby Memorial Medal for academic excellence.

During his Ph.D., Swanson parameterized forcefields for the simulation of peptoids, synthetic peptide analogs of peptides. A notable outcome of this published work was the development of the first extensible coarse-grained molecular dynamics (CG-MD) forcefield for peptoids. He also contributed to the development and successful application of an innovative method for the simulation of reactive peptide self-assemblies, and rationalized connections between discreet molecular architecture and observed supramolecular self-assembly outcomes.

Swanson’s current work seeks to elucidate how the molecular architecture of peptide amino acid sequences influences their intermolecular interactions and how these interactions, in turn, affect material properties such as solubility and the tendency to self-assemble. To do this, he utilizes molecular dynamics (MD) simulations and theoretical approaches to probe the molecular conformation of peptides. By working closely with experimental colleagues within the Ulijn lab, Swanson is able to benchmark the insights gained from these investigations and move towards the goal of developing a syntax with which to rationally design peptide-based materials. He is developing improved descriptors for MD simulation analysis and plans to leverage machine-learning methods to predict peptide properties and generatively discover new sequences for desired material properties.