Admission process: Students applying for the MSc in Industrial Engeneering and Management program can connect by writing to email@example.com for any assistance and information.
Admission Cycle: Applications will be accepted until July 15th 2022
Admission Requirements: The program requires students to have A Bachelor’s degree in Industrial Engineering and management with a grade average of 80 or above, or students must be ranked in the top 25% of their class. Applications of students having a bachelor’s degree averaging at least 80 in other fields of engineering, exact sciences, economics, and behavioral sciences, and who are in the top 25% of the class, will be brought before the Admissions Committee for discussion. For those makeup courses my be required.
Students with a bachelor’s degree average of 75-80 in these fields may apply through an admissions committee and attach two letters of recommendation. Students are required to present a score of at least 6.5 and above on the IELTS English proficiency test.
Ariel University reserves the right to make changes to the admission terms
The Masters in Industrial Engineering and Management is a research-intensive program curated to offer students a range of engineering subjects and quantitative analysis techniques. These include planning, design, control, and management of complex organizations and systems.
The master’s program equips engineering students with a know-how that stresses innovation, how to find optimal processes to enhance productivity in manufacturing and service industries. The students study a wide range of quantitative and qualitative topics that provides them a comprehensive education in subjects such as operations research and statistics, performance measurement and productivity, autonomous vehicles and robotics, engineering production and management, machine learning and artificial intelligence, inventory control, and distribution systems, ergonomics and human factors.
Taught entirely in English, the two-year research-intensive program offers students with three areas of specialization –
- Human Factor Engineering
- Knowledge and Data Engineering
Autonomous systems and robotics focus on defining capabilities, motion planning of autonomous vehicles, navigating robots in a plane under uncertainty, searching for targets in probabilistic space, the motion of robotic swarms and topological methods, and their uses for analyzing single motion and cluster motion.
Human factor engineering focuses on work environment design, effective movement, movement volumes, measurement, performance improvement, and efficiency characterizations, physiological, psychological, and functional stress, human performance ability, human-looking interfaces and limitations, and decision-making in control and monitoring systems.
Knowledge and data engineering, one of the recently emerging fields combines algorithms for dealing with vast information, statistical prediction methods, machine learning, and “deep learning” algorithms to enable the transformation of raw data to models that predict, foretell, and draw conclusions.