This advanced PhD course focuses on equipping doctoral students with a robust understanding of stochastic models and their applications in operational decision-making. The curriculum delves into the complexities of decision-making under uncertainty, introducing students to sophisticated techniques such as dynamic programming for sequential decision processes. Key areas of application include inventory control, pricing strategies, and financial management, with a particular emphasis on bridging the gap between high-level financial objectives and operational guidelines. The course explores the profound impact of uncertainty on operational decisions, providing students with the analytical tools to navigate complex business environments. Through a combination of theoretical foundations and practical problem-solving, students will develop proficiency in fundamental models and technical solution methods essential for Operations Research and Operations Management research. This course serves as a cornerstone for PhD candidates, preparing them for advanced research in stochastic modeling and its real-world applications in management science.