Position 1 (MSc/PhD): Modeling Interfacial Reaction-Diffusion in Electrochemical Systems
We seek a highly motivated candidate to develop dynamic density functional theory (DDFT)-based models of interfacial reaction-diffusion processes in electrode systems. This work will focus on transport phenomena at the electrolyte-electrode interface and applications in corrosion prevention, electric double-layer capacitors, and advanced electrolyte design. The ideal candidate has experience in computational physics/chemistry, partial differential equations, and machine learning. Familiarity with DFT, DDFT, or electrochemical modeling is highly desirable.
Position 2(MSc/PhD) : Computational modelling of Two-photon photosensitizers for photodynamic therapy
We are looking for a candidate to work on the computational modeling of two-photon photosensitizers using time-dependent density functional theory (TD-DFT) methods. These photosensitizers are designed to enhance the efficiency of photodynamic therapy (PDT), a treatment that uses light-activated molecules to generate reactive oxygen species for targeting and destroying diseased cells. By employing TD-DFT, this project aims to predict and optimize the photophysical properties, such as two-photon absorption cross-sections and excited-state dynamics, of potential photosensitizers. The findings will guide the design of novel molecules with improved two-photon activity, ensuring better performance in clinical PDT applications.
Qualifications:
- Strong programming skills (e.g., Python, C++, or Julia).
- Experience with computational modeling frameworks and machine learning tools.
- Demonstrated ability to work independently and collaboratively.
If interested, please submit your CV, a brief statement of research interests, and references to cgtetsas@uwaterloo.ca