A fully funded PhD position in Computational Science is available at Middle Tennessee State University (MTSU) under the supervision of Assistant Professor Mohammad Arif Hossain. The research focuses on advanced topics such as AI for Cybersecurity and LLM-security, AI-Native Next-Generation Networks (6G and Beyond), Agentic AI for Network Automation, AI for Edge Computing and Distributed Intelligence, and Quantum Machine Learning. The selected candidate will engage in cutting-edge research on secure and intelligent wireless systems, agentic AI for autonomous network decision-making, distributed intelligence, and quantum-assisted intelligence for next-generation networks. This opportunity offers strong prospects for high-impact publications and hands-on experience in machine learning, security, and network automation. The ideal applicant will have a background in computer science, computer engineering, or a related field, with strong programming skills in Python and machine learning frameworks such as PyTorch or TensorFlow. Experience with machine learning is required, and familiarity with wireless networks or cybersecurity is preferred. Candidates should be highly motivated, research-driven, innovative, and eager to publish in top venues. The position is fully funded, covering tuition and providing a stipend (exact amount not specified). The application deadline is December 28, 2025, for Fall 2026 entry. To apply, candidates should email a single PDF containing their CV, transcripts, a brief statement of research interests, and optionally a sample publication to [email protected]. Research areas include: Computational Science, Artificial Intelligence, Cybersecurity, LLM-security, Next-Generation Networks, 6G, Agentic AI, Network Automation, Edge Computing, Distributed Intelligence, Quantum Machine Learning, Wireless Systems, and Machine Learning. This position is ideal for students interested in the intersection of AI, security, and advanced networking technologies.