Cost & earnings at University of Iowa What students borrow here, and what they go on to earn
Applied Mathematics graduates earn a median $54,463 Across 313 US programmes, two years after finishing
See the degree grade →The PhD in Applied Mathematics at the University of Iowa is a research-led programme that trains students to develop mathematical models, analytic techniques and computational methods for real-world problems. It suits candidates with a strong mathematical background who want to pursue original research and careers in academia, industry or government research laboratories.
The PhD programme combines advanced coursework, qualifying examinations, research seminars and an original dissertation. Core topics commonly studied include partial differential equations, numerical analysis and scientific computing, dynamical systems, optimisation, inverse problems, stochastic processes and mathematical modelling in the physical and life sciences. Students typically take a mix of required graduate-level courses and electives to support their research focus.
Applicants should hold a bachelor’s degree in mathematics or a closely related discipline; a master’s degree with substantial graduate coursework in mathematics is commonly expected or recommended. Successful candidates demonstrate strong preparation in advanced calculus/real analysis, linear algebra, differential equations and numerical methods.
Graduates of the PhD in Applied Mathematics pursue diverse careers. Many continue in academia as postdoctoral researchers and faculty members. Others take research scientist or data scientist roles in industry—such as finance, engineering, energy, technology and pharmaceuticals—or positions in government and national laboratories.
The University of Iowa offers a supportive research environment within a mathematics department that hosts experts in analysis, numerical methods, dynamical systems and interdisciplinary modelling. Students benefit from close mentorship, regular seminars and opportunities to collaborate with neighbouring departments such as engineering, physics, statistics and the life sciences.
Facilities and resources include access to campus computational resources and high-performance computing, as well as opportunities to engage with applied research centres and labs on campus. The programme emphasises both rigorous theoretical training and practical computational skills, preparing graduates for research and applied careers across sectors.
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