Here are two PhD projects I will be offering starting in September 2016.
1. Evolution of antibiotic resistance in bacterial colonies
One of the factors that affects how microbes evolve resistance to antibiotics in their natural environment are mechanical cell-cell and cell-surface interactions. Although still underappreciated by biologists, such interactions have been shown to play a huge role in determining the growth of microbial colonies [1,2]. This project will have three aims: (i) to understand how physical properties (stiffness, adhesion, etc.) of individual bacteria affect how these cells interact in a colony, (ii) to find out how these properties affect the rate at which resistant mutations fix in the population of bacteria, and (iii) to try to change these properties to reduce the risk of resistance evolution.
The project will be mostly experimental but it may also involve a modelling component (computer simulations), and a collaboration with Edinburgh researchers Rosalind Allen and Davide Marenduzzo. Prior knowledge of microbiology is not required but a strong motivation for interdisciplinary work is desired.
 F.D.C. Farrell, O. Hallatschek, D. Marenduzzo, B. Waclaw, Phys. Rev. Lett. 111, 168101 (2013).
 M.A.A. Grant, B. Waclaw, R.J. Allen, P. Cicuta, J. R. Soc. Interface. 11 (97), 20140400 (2014).
2. Computer models of solid tumours
Modelling cancer has a long history, but only recently researchers began to look at the genetic composition of solid tumours. This is in part motivated by the perceived relationship between genetic heterogeneity of a tumour and the likelihood that chemotherapy will fail to eradicate it. More heterogeneous tumours will harbour more genetic mutations, some of them making cells resistant to treatment. Recently, a simple three-dimensional lattice model  demonstrated that heterogeneity is affected by three processes: replication and death of cells, and cellular migration.
The aim of this project will be to develop a more realistic, physics-based, off-lattice model, and use it to investigate how the risk of chemotherapy failure could be minimized. Besides genetic heterogeneity of cancer cells, the model will have to account for a heterogeneous distribution of the chemotherapeutic agent – it has been shown that drug gradients play a major
role in speeding up the evolution of resistance .
The project will involve collaboration with Edinburgh researchers (Tibor Antal) as well as overseas groups led by Martin Nowak (Harvard), and Bert Vogelstein (Howard Hughes Medical Institute).
 B. Waclaw, I. Bozic, M.E. Pittman, R.H. Hruban, B. Vogelstein, M.A. Nowak, Nature 525 (7568), 261-264 (2015).
 P. Greulich, B. Waclaw, and R. Allen., Phys. Rev. Lett. 109, 088101 (2012).