Learn about Industry and Government Careers

  • Jobs on Toast - Resource hub where researchers and university careers staff can find web pages, articles, podcasts and books to help them overcome common career challenges.
  • Versatile PhD - Resource to help graduate students, ABDs and PhDs identify, prepare for and excel in professional careers.
  • From PhD to Life - Read a selection of transition stories in their Transition Q & A series.
  • We Use Math - List of careers and industries that use mathematics.
  • Society for Industrial and Applied Mathematics (SIAM) at Illinois
  • Institute for Operations Research and Management Sciences (INFORMS) at Illinois
  • Talk with people and ask questions! Talk with alumni online and at the departmental reception at the AMS Joint Math Meetings (JMM), talk with the Director of Graduate Studies about your interest in industry or government careers, talk with as many people as possible among your friends, family and academic network. Many people will help and offer advice if you explain what you want to know. 

Prepare for Careers

Resumes and interviewing:

Technical skills:

Acquire basic coding and statistical skills – take some courses on campus at whatever level gets you started. Possibilities include:

  • STAT 200 Statistical Analysis
  • STAT 207 Data Science Exploration
  • STAT 425 Applied Regression and Design
  • STAT 440 Statistical Data Management
  • STAT 448 Advanced Data Analysis
  • STAT 542 Statistical Learning (highly recommended). Theory and proof of popular machine learning algorithms, with practical implementation homework. The end-of-semester project is good for your CV.
  • CS 307 Modeling and Learning in Data Science
  • CS 446 Machine Learning
  • CS 512 Data Mining
  • CS 598 Machine Learning for Signal Processing (topics course)
  • Machine learning courses in the CS department

For students who need numerical methods:

  • CS 101 – Intro Computing: Engrg & Sci (tools course, scientific computing, C, Matlab, Unix/Linux)
  • CS 357 – Numerical Methods I (theoretical, Python, Mathematica, Matlab, course for large scale programming)
  • CS 450 – Numerical Analysis (theoretical)
  • CS 555 Numerical Methods for PDEs

For students who need programming exposure and not numerical methods:

  • CS 125 – Intro to Computer Science (Java, object oriented programming)
  • CS 173 – Discrete Structures (prereq for CS 225)
  • CS 225 – Data Structures (C++, object oriented programming)

Online training options include:

Internships

Summer internships get you experience and recommendations from people working in industry.

Internship programs:

  • IMSI - based at University of Illinois; scientific lab placements.
  • NSF - grant supplements for internships

Government labs:

Industry internships:

Jobs

Miscellaneous links