Conduct research in fundamental mathematics or in application of mathematical techniques to science, management, and other fields. Solve problems in various fields using mathematical methods.
Dynamic power management for a hydropower facility with multiple turbines. EWU students built optimization models that balance load across turbines in real time.
Linear programmingNonlinear programmingMATLABComputational optimization
Outcome: MAA-sponsored industry partnership
Columbia Lighting LitePro
Ongoing
Partner: Columbia Lighting R&D
Custom radiosity software for computing light intensities in critical environments. Alumnus-led project that took applied mathematics from theory to shipping production code.
Employ the appropriate numerical technique to approximate a solution of an initial value problem, boundary value problem, or partial differential equation, with careful consideration of initial or boundary data.
Demonstrate the ability to analyze algorithms to interpolate data with polynomials.
Compute local truncation error and understand its relationship to the global error in a given numerical scheme.
Construct finite-difference schemes in order to approximate solutions to differential equations and analyze their order of approximation
Apply differential and integral calculus techniques to trigonometric functions, exponential functions, logarithmic functions and the inverses of these functions
Implement an iterative method to solve a problem (e.g. matrix decomposition, solution of a linear system of equations, determining eigenpairs of a matrix)
Provide details of backward stability analysis of an iterative scheme;
Employ the appropriate numerical technique to approximate a solution of an initial value problem, boundary value problem, or partial differential equation, with careful consideration of initial or boundary data.
Demonstrate the ability to analyze algorithms to interpolate data with polynomials.
Implement an iterative method to solve a problem (e.g. matrix decomposition, solution of a linear system of equations, determining eigenpairs of a matrix)
Apply differential and integral calculus techniques to trigonometric functions, exponential functions, logarithmic functions and the inverses of these functions
Apply differential and integral calculus techniques to trigonometric functions, exponential functions, logarithmic functions and the inverses of these functions
Demonstrate knowledge of relationships between exponents and logarithms and their derivatives
Demonstrate the ability to perform integration by applying one of the following techniques: Powers of trigonometric functions, Trigonometric substitution, Algebraic substitution, Method of parts, Partial fractions for the linear and the quadratic case
use numerical schemes to find approximate solutions to initial value problems utilizing mathematical software such as Matlab or Mathematica.
set up and solve second order, constant coefficient differential equations that arise from physical systems such as mass-spring systems and RLC circuits. In addition, students will have a strong intuition of the phenomenon of resonance.
Employ the appropriate numerical technique to approximate a solution of an initial value problem, boundary value problem, or partial differential equation, with careful consideration of initial or boundary data.
Implement an iterative method to solve a problem (e.g. matrix decomposition, solution of a linear system of equations, determining eigenpairs of a matrix)
Model a physical signal by using mathematical functions, and solve the equations when excited by an arbitrary function.
Describe each of the following system categories: Linear, nonlinear, time-invariant, time-varying, causal, noncausal, memoryless, continuous-time, discrete-time etc.
use numerical schemes to find approximate solutions to initial value problems utilizing mathematical software such as Matlab or Mathematica.
set up and solve second order, constant coefficient differential equations that arise from physical systems such as mass-spring systems and RLC circuits. In addition, students will have a strong intuition of the phenomenon of resonance.
Employ the appropriate numerical technique to approximate a solution of an initial value problem, boundary value problem, or partial differential equation, with careful consideration of initial or boundary data.
Demonstrate the ability to analyze algorithms to interpolate data with polynomials.
Apply differential and integral calculus techniques to trigonometric functions, exponential functions, logarithmic functions and the inverses of these functions
Demonstrate knowledge of relationships between exponents and logarithms and their derivatives
Apply differential and integral calculus techniques to trigonometric functions, exponential functions, logarithmic functions and the inverses of these functions
Understand the development of the natural logarithmic function
set up and solve second order, constant coefficient differential equations that arise from physical systems such as mass-spring systems and RLC circuits. In addition, students will have a strong intuition of the phenomenon of resonance.
use numerical schemes to find approximate solutions to initial value problems utilizing mathematical software such as Matlab or Mathematica.
Demonstrate a conceptual knowledge of the derivative as a limit of slopes of secants, as the slope of non-vertical tangents and as the rate of change of one quantity with respect to another
Employ the appropriate numerical technique to approximate a solution of an initial value problem, boundary value problem, or partial differential equation, with careful consideration of initial or boundary data.
Demonstrate the ability to analyze algorithms to interpolate data with polynomials.
Employ the appropriate numerical technique to approximate a solution of an initial value problem, boundary value problem, or partial differential equation, with careful consideration of initial or boundary data.
set up and solve second order, constant coefficient differential equations that arise from physical systems such as mass-spring systems and RLC circuits. In addition, students will have a strong intuition of the phenomenon of resonance.
Demonstrate a conceptual knowledge of the derivative as a limit of slopes of secants, as the slope of non-vertical tangents and as the rate of change of one quantity with respect to another
5 most recent CareerOneStop listings for this occupation. "Live" in Quick Facts counts only postings the scraper re-confirmed in the last 7 days; older real postings still appear here until they age out.
Course evidence covers every O*NET task we tracked
Every O*NET task for this occupation has at least one candidate
course match in the EWU Math BS catalog (matched at cosine
similarity ≥ 0.30 against course learning outcomes). Faculty
review of individual matches is ongoing. Electives extend that
preparation further.
More O*NET details for this occupation
(skills, knowledge, tools & technology)
Analytical or scientific software: Analysis and Visualization of Time Sequences AVTS
Analytical or scientific software: Apfloat
Analytical or scientific software: Apple Shazam
Analytical or scientific software: Aptech Systems GAUSS
Analytical or scientific software: Aztec
Analytical or scientific software: Computer Algebra System for Algebraic Geometry CASA
O*NET's tools-and-technology list aggregates software encountered
across the occupation's many sub-roles, so the list can be broad.
Treat it as a directory of what people in this job might
use, not a checklist of what every job requires.
Where this data comes from.
Occupation descriptions, tasks, skills, and education-incumbents survey
come from the U.S. Department of Labor's
O*NET 30.2.
Washington-state pay and employment projections come from
WA Employment Security Department
and the
BLS Occupational Employment and Wage Statistics.
Live job postings come from
CareerOneStop,
refreshed nightly from a scrape that tracks the original posting date
and the date our system last saw each posting live.
How we connect courses to occupations.
Course catalog descriptions and program-level learning outcomes are
indexed alongside O*NET task statements. Where a course's language
aligns with a task an occupation requires, we mark it as evidence
of preparation. Faculty review each candidate match and either
confirm or veto it; only confirmed matches surface in totals.