Doctor of Philosophy (Ph.D.) in Civil and Environmental Engineering - Dynamic Systems, Uncertainty, and Optimization 72 months PHD Program By Duke University |Top Universities

Doctor of Philosophy (Ph.D.) in Civil and Environmental Engineering - Dynamic Systems, Uncertainty, and Optimization

Program Duration

72 monthsProgram duration

Main Subject Area

Built EnvironmentMain Subject Area

Program overview

Main Subject

Built Environment

Study Level

PHD

Curriculum: Research degree comprised of advanced technical coursework and or a doctorate (PhD) in a chosen discipline. Professional Interests: Research or technology development in academia, industry, or government. Duration: Average is 6 years Ideal Candidates are: Interested in leading specialized research efforts in academia, industry or a government lab Motivated to publish peer-reviewed research with faculty advisers Prepared to present research efforts to professional and technical societies at conferences Interested in careers that focus on research and technology development Willing to work in a highly collaborative, interdisciplinary environment Dynamic Systems, Uncertainty, and Optimization Dynamics are prevalent in the mechanics of diverse engineered and natural systems and system failures often depend on factors that can only be estimated with considerable uncertainty. The engineering (or optimization) of failure mitigation measures therefore re- quires modeling the transient dynamic aspects of failure mechanisms, the uncertainties in system capacities and, importantly, the uncertainties in system loading. This graduate concentration focuses on modern methods of dynamic systems analysis, numerical modeling, and parallel computing: tools that can be used to quantify risks with unprecedented realism. The curricular program leverages premier courses in the core disciplines of applied mathematics, numerical methods, uncertainty modeling, and mechanics.

Program overview

Main Subject

Built Environment

Study Level

PHD

Curriculum: Research degree comprised of advanced technical coursework and or a doctorate (PhD) in a chosen discipline. Professional Interests: Research or technology development in academia, industry, or government. Duration: Average is 6 years Ideal Candidates are: Interested in leading specialized research efforts in academia, industry or a government lab Motivated to publish peer-reviewed research with faculty advisers Prepared to present research efforts to professional and technical societies at conferences Interested in careers that focus on research and technology development Willing to work in a highly collaborative, interdisciplinary environment Dynamic Systems, Uncertainty, and Optimization Dynamics are prevalent in the mechanics of diverse engineered and natural systems and system failures often depend on factors that can only be estimated with considerable uncertainty. The engineering (or optimization) of failure mitigation measures therefore re- quires modeling the transient dynamic aspects of failure mechanisms, the uncertainties in system capacities and, importantly, the uncertainties in system loading. This graduate concentration focuses on modern methods of dynamic systems analysis, numerical modeling, and parallel computing: tools that can be used to quantify risks with unprecedented realism. The curricular program leverages premier courses in the core disciplines of applied mathematics, numerical methods, uncertainty modeling, and mechanics.

Admission Requirements

7+
Other English language requirements : TOEFL with a paper-based score of 577.

72 Months
Jan-2000

Tuition fees

Domestic Students

0 USD
-

International Students

0 USD
-

Scholarships

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