Funded positions in particle-based cancer cell modeling

PhD student and postdoctoral positions are currently available with a starting date in January 2018 or later. The positions are fully funded.

The successful candidates will work on the development of particle-based model for simulation of cells in health and disease (cancer).

Candidates should have strong programming skills (C++, GPU), background in numerical methods, and a degree in Applied Mathematics, Physics, Chemistry, Computer Science or a relevant engineering discipline.

About the project:

Cancer metastasis, i.e. the process by which cancer spreads from its original place, is an important problem attributed to nine out of ten cases of cancer deaths. The agents of this process are circulating tumor cells (CTCs). During an hematogenous metastasis CTCs intravasate into the leaky vasculature around the tumor and eventually enter the bloodstream. After circulating for an unknown amount of time, the CTCs extravasate from the vasculature and grow secondary tumors. The detection of CTCs in the blood is one of the most potent methods for the early diagnosis of cancer and a key target of liquid biopsies. However, with 1 CTC present for every 10^9 red blood cells (RBCs), this detection is a difficult task.

CTC behavior in the blood stream is attributed primarily to it’s mechanical properties. The metastatic potential is directly connected to the deformability of a CTC. Normal cancer cells are typically more deformable than benign cells. The large variety of the cancer tumor types determines the diversity of the corresponding CTCs mechanical properties.

Predictive simulations of the CTC flow in microfluidic devices and capillary networks might help to quantify the impact of different aspects of cell mechanics on it’s invasive potential. The aim of this project is to develop computational framework for the simulations of cells with nucleus and cytoskeleton in flows in complex domains, such as capillary networks and microfluidic devices. In order to achieve this goal, we are developing a new cell model and software efficiently exploiting modern supercomputers. The model will be extensively validated using quantitative experimental data provided by our collaborators. The proposed model parameterization will have the flexibility to be used in simulations of various cell types.

The new model will allow to study in silico numerous problems related to the cell biomechanics in flows, including investigation of the efficiency of different microfluidic devices in terms of CTC filtering and detection, as well as subsequent design optimization leading to increase in device performance. The model may also be valuable for investigation of CTC transport in microvasculature, and with further development may help to elucidate mechanical forces that CTC has to withstand during its journey to distant sites in the body, possibly directing to new strategies in cancer treatment.