MS Research Opportunities (2 Positions Available) | Advanced Intelligent Manufacturing Systems (AIMS) Lab | Bowling Green State University
The AIMS Lab (PI: Dr. Tusar), within the School of Engineering at the College of Engineering and Innovation, Bowling Green State University (BGSU), is seeking two highly motivated MS students to join the lab starting in Spring 2027.
Feel free to explore the AIMS Lab Website to learn more about our past and ongoing research.
Links: https://sites.google.com/view/imrantusarphd/aims-lab/about?pli=1&authuser=0 & https://www.bgsu.edu/engineering-and-innovation/about-the-college/faculty-and-staff-directory/imran-tusar.html
Research Focus Areas:
• Machine Learning, Deep Learning and Artificial Intelligence
• Intelligent & Smart Manufacturing and Supply Chain Systems
• Data-driven Modeling, Optimization, and Decision Support
What This Position Offers:
• Thesis-based MS with close faculty mentorship with strong publication and PhD preparation pathway
• BGSU is surrounded by major automotive and advanced manufacturing companies, enabling strong internship and employment opportunities
• Most students secure internships by the 2nd year, often leading to full-time roles
• Diligent students can complete the MS in as early as 1.5 years with proper guidance
Eligibility & Admission Highlights:
• GRE is NOT required
• Minimum English proficiency: TOEFL iBT: 80 / IELTS: 6.5 / PTE: 53 / Duolingo: 110
• Preferred Background: Industrial Engineering, Computer Science, Data Science, or related fields
• Strong interest in AI, optimization, manufacturing or supply chain systems
• Programming experience (Python or R preferred)
Stipend/ Scholarship:
Full tuition coverage is provided through the stipend, with additional scholarship support available for eligible students.
How to Apply:
Interested students should email the following to mtusar@bgsu.edu with subject line: AIMS Lab Applicant Spring 2027
• CV/Resume
• Brief statement of research interests
• Academic transcripts (unofficial copies acceptable initially)
• Prior research publications (if any)
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