Position: Junior Python Developer
Category: Python
English level: upper
Years of experience: 0.5


One of my first projects was K-means Clustering. In this project, I implemented the K-means Clustering algorithm using Python. K-means Clustering is an unsupervised machine learning technique that groups similar data points based on their features. It finds applications in diverse domains such as data analysis, image segmentation, and customer segmentation.

Another project of mine was Speed Detection. For this project, I developed a speed detection system using Python and computer vision techniques. The primary goal was to accurately determine the speed of cars in real-time through camera feeds.

Starting from August 2023 and continuing to the present, I have been a member of the MRI Field Simulation Project at Forschungszentrum Juelich in Germany. In this project, I contribute to the advancement of magnetic resonance imaging (MRI) with a focus on ultra-high field imaging. My role involves implementing optimal control theory to counteract magnetic field inhomogeneity using parallel excitation pulses, particularly the "GRAPE" pulse. This involves utilizing MRI scanner field maps, evaluating pulse performance through simulations and actual MRI measurements, and aiming to enhance image quality and homogeneity.