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Mozhdeh currently serves as a Research Fellow at the University of Southampton's School of Mathematical Sciences, specializing in the application of artificial intelligence (AI) and mathematical modeling to investigate life-course determinants, development, and prevention of early-onset burdensome multimorbidity. Her primary responsibilities include the development of machine learning models tailored to early-onset burdensome multimorbidity. Mozhdeh's work focuses on leveraging data from birth cohorts and routine healthcare datasets to discern early-life determinants of multimorbidity. Her research is instrumental in advancing the understanding of the intricate factors contributing to early-onset burdensome multimorbidity, offering valuable insights to inform preventative strategies. With expertise in the intersection of cutting-edge technology and healthcare research, Mozhdeh applies her knowledge to pave the way for innovative solutions that address critical public health issues. Her contributions have far-reaching implications for improving the lives of individuals affected by this health condition. Her academic trajectory includes a diverse background in mathematics, information science, technology, and a Ph.D. in chemical engineering, where she focused on applying machine learning techniques to simulate water metal-oxide interfaces.