Stacks Image 63
Graduate Research Opportunities
We are looking for highly motivated and talented graduate students with interests in computational materials science and/or biophysical simulation for research opportunities in:

  • Mesoscale simulation, machine learning, and inverse design of self-assembling organic electronics
  • Computational vaccine design for hepatitis C virus and flu
  • QSAR design of antimicrobial cell penetrating peptides

Prior experience in computer programming or molecular simulation is desirable but not necessary. A strong background in mathematics and physical sciences is required.

Interested students should contact Prof. Ferguson directly at
alf@illinois.edu for more information enclosing a current (unofficial) transcript and CV.
Undergraduate Research Opportunities
We are looking for highly motivated and talented UIUC undergraduates from all departments for the following research opportunities available for academic year 2017-18. Interested undergraduate students from all departments should contact Prof. Ferguson directly at alf@illinois.edu enclosing a current (unofficial) transcript and CV.

1. Mesoscale molecular simulations of self-assembling organic electronic nanowires

Certain biological molecules containing aromatic rings can self-assemble into 1D nanowires possessing overlapping π orbitals, which leads to electron delocalization and interesting conductive, optical, and photophysical properties. These organic electronic nanoaggregates have a variety of applications, from organic photovoltaic cells to the LEDs found in the new Apple watch. This project will use mesoscopic molecular dynamics simulations and machine learning to understand the self-assembly of a family of optoelectronic peptides to determine the molecular-level effects of changing chemistry on aggregate structure and properties.

This undergraduate research position requires a strong background in physical sciences, and familiarity with Linux, bash shell, and Matlab. No prior knowledge of biology or chemistry is required.

2. Molecular design of self-assembling antimicrobial nanostructures

Antimicrobial resistance poses a serious public health issue, affecting millions and costing over $55 billion in annual health care costs in the United States alone. We are interested in designing alternative treatments to traditional drug therapy using self-assembling nanostructures formed from short amphiphilic peptides that have been shown to preferentially bind to bacterial cell walls and induce cell lysis and death. This project will use mesoscale molecular simulation of these short peptides alongside machine learning to understand the effects of peptide sequence on aggregate structure, thermodynamics, and kinetics.

Qualified applicants for this undergraduate research position will possess a strong background in physical sciences and familiarity with Linux, Python, and Matlab. C/C++ experience is welcome. No prior knowledge of biology or chemistry is required.