Hello everyone, The Lab: The Korani Lab in the Department of Data Science at the University of North Texas (UNT) is recruiting two PhD students to start in Fall 2026. Our research sits at the intersection of Computational Neuroscience, Biomedical Signal Processing, and Explainable AI. We focus on developing diagnostic tools to predict and detect mental disorders (Major Depressive Disorder) and evaluate treatment outcomes (rTMS, SSRI) using high-dimensional EEG data. The Project: The successful candidate will work on building and optimizing custom CNN and RNN architectures to decode complex patterns in EEG signals. This is not just applying off-the-shelf models; we are developing novel optimization algorithms (e.g., Mother Tree Optimization) and fusion techniques to improve diagnostic accuracy and interpretability in clinical settings. We are looking for: * Background: BS/MS in Computer Science, Electrical Engineering, Computational Neuroscience, or a related quantitative field. * Technical Skills: Strong proficiency in Python (PyTorch/TensorFlow) and MATLAB. * Domain Knowledge: Experience with Time-Series Analysis or Signal Processing is highly desired. Prior work with EEG data is a significant plus. * Math: Comfort with linear algebra and optimization theory. Why Join? * Impact: Your code will directly contribute to tools intended for clinical use to improve mental health treatment outcomes. * Environment: UNT is a Tier 1 Research University. You will collaborate with clinical partners (including international collaborations) and have access to large-scale clinical datasets. To Apply: Please email a CV, transcripts (unofficial are fine), and a brief statement of research interests to Dr. Wael Korani ([wael.korani@unt.edu]). Please use the subject line: "PhD Application Fall 2026 – [Your Name]". Review of applications will begin immediately and continue until the two positions are filled. Dr. Wael Korani Assistant Professor Department of Data Science University of North Texas [Link to your Faculty Profile or Lab Website]