IMU 2012 - 2012 IEEE 5th International Measurement University (IMU)

The IMU accepts new and prior IMU students each year to participate in the week long program. Each year the fundamentals of measurement science are reviewed in addition to a varying rotation of different higher level topics related to measurement systems and processes. IMU is designed to provide a full and exhaustive picture of I&M fundamentals and multi-disciplinary applications. IMU provides a good balance between fundamental and higher level knowledge to ensure that one-time attendees and prior attendees will both gain the maximum benefit. Participants will be given the opportunity to have one on one time with the university faculty and speakers to discuss problems specific to their area of research and their projects, in addition to getting mentoring advice as needed. The IMU’s organized social activities will provide an additional opportunity for attendees to interact with speakers and fellow attendees to build international collaborative networks to aid their current and future measurement challenges related to academic research or industrial process.

In addition to learning about measurement techniques and forming collaborative networks, IMU also offers its attendees the opportunity to earn continuing education credits which can be applied to university transcripts (if applicable) or be provided to their employer.
IMU is accepting applications from:

Ph.D. candidates undertaking a course of study and research in all scientific and technical fields, needing to expand and gain additional knowledge in the I&M field and techniques.
Entry-level engineers working in all fields, needing to quickly master the fundamentals of measurement to optimize the design and monitoring of process systems, instrumentation development, or any multidisciplinary projects where measurements are made.
IMU is interested in applicants who:

are interested in learning techniques to characterize the performance of their data collection techniques, measurement systems, or models, according to the modern uncertainty approach followed by the present Standards
need to learn optimization techniques to improve their measurement systems and models used in laboratory research or industrial projects
would like to learn how to improve their data collection and measurement techniques by reducing uncertainty propagation.