Dr. Lazebnik's lab focuses on the mathematical modeling of personalized medicine in its broadest sense. They use mathematical and computational methods, such as simulations, machine learning, differential equations, and stochastic processes, to address challenges in personalized medicine.

In the field of scientometrics, Dr. Lazebnik's lab is leading research projects about the usage of AI methods to study scholars' career development and practices as well as data-driven methods to understand relationship dynamics between scholars.

The lab seeks students with recent academic experience, ideally with a paper published in a Q1/Q2 journal in the last two years. A strong background in programming (preferably Python and JavaScript), machine learning, and mathematical modeling is essential. For funded positions, full-time commitment is required. Otherwise, one full day per week is acceptable. Importantly, the lab maintains very high standards, aiming for high-impact and timely research.

For more details, please read the following join the lab page on Dr. Lazebnik's website.