Current opening
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) : Modeling Tissue Dynamics Using DDFT
We are looking for a candidate to develop dynamic density functional theory, DDFT-based models of tissue dynamics, incorporating features such as proteins and membrane deformations. Using physics-informed machine learning, this project will explore nanoscale biological processes, including intracellular signaling and tissue morphogenesis. Applicants should have a background in computational biology, biophysics, or applied mathematics, with experience in PDEs, multiscale modeling, or molecular dynamics simulations.
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 .