Multiple PhD Positions in Industrial Data Analytics_OSU_2023 Spring or Fall

Oklahoma State University (OSU) 工业工程系助理教授Akash Deep招收2023 Spring/Fall 全奖PhD. 数据分析方向。

The School of Industrial Engineering & Management (IEM) at Oklahoma State University (OSU) is looking for two highly motivated individuals interested to pursue doctoral degree in Industrial Engineering, with the focus in Industrial Data Analytics. Students will work towards the development of data-driven methodologies for smart and connected systems, and complex business processes. Broad research directions are as follows:• Advanced data analytics for IoT-enabled smart and connected systems.
• Stochastic modeling, prognosis, and control for event data.
• Reliability modeling and maintenance planning for complex engineering systems.
• Real-time monitoring and automation of business service processes.

The positions are fully funded and begin in Spring-23/Fall-23 semester. Interested
candidates, please review the requirements below.

Requirements:
- A B.S. or M.S. degree in Industrial Engineering, Statistics, Operations Research,
Computer Science, Mathematics, Management Science, or a related discipline.
- Strong competence in at least one programming language (R, Python, MATLAB
preferred).
- Meet the general school's requirements (https://go.okstate.edu/graduate- ... management-phd.html).
- Excellent written and oral communication skills

How to Apply:
If you meet the above requirements and are interested, please email (1) a detailed CV, (2) a cover-letter describing your (past/current) research experiences, (current/future) research interests and goals, and (3) sample publications such as, preprints, accepted manuscripts, white pages, thesis etc. (optional), to Dr. Akash Deep at akash.deep@okstate.edu. Selected applicants will be contacted and interviewed virtually.

About PI:
Dr. Akash Deep received his Ph.D. in Industrial Engineering and M.S. in Statistics from the University of Wisconsin-Madison. He obtained his B. Tech degree in Production and Industrial Engineering from the Indian Institute of Technology Roorkee, India. His research broadly belongs to the realm of industrial data analytics, focusing specifically on methods for predictive analytics for intelligent maintenance, data-driven operations planning for production systems, and monitoring and anomaly detection of service processes. During his Ph.D., he served as the lead researcher for several industry-sponsored projects. He is a recipient of the E. Wayne Kay Graduate Scholarship from the Society of Manufacturing.

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