Sungjun Kim

Dongguk University in Seoul, South Korea is advertising a PhD position for Fall 2026 in a research group led by Professor Sungjun Kim . The project focuses on AI hardware , neuromorphic computing , and in-memory computing systems , with related interests in neural networks, deep learning, hardware-aware AI algorithms, AI accelerators, and edge AI. Preferred applicants have backgrounds in computer engineering, electrical engineering, hardware algorithms, neural networks, or AI systems. The post specifically notes that candidates from device fabrication, materials synthesis, or materials characterization are generally not the target for this recruitment. This is a PhD opening rather than a postdoctoral or research professor position, and the poster prefers applicants for the regular PhD program instead of an integrated MS–PhD track. According to the admission notice, the online application period is June 25, 2026 to July 3, 2026 , and supporting documents must be submitted by July 6, 2026 . The intended start date is September 1, 2026 . Interested candidates should review the graduate school admission information and contact Professor Sungjun Kim with a CV and a brief description of research experience.

Dongguk University in Seoul, South Korea is recruiting 2–3 PhD students for Spring 2027 admission (March 2027) in a research group led by Professor Sungjun Kim. The opening focuses on AI / Computer Engineering and Semiconductor Devices . Research topics include deep learning, neural networks, hardware-aware AI, AI accelerators, edge AI, neuromorphic computing, in-memory computing, computer architecture, hardware/software co-design, modeling and simulation, as well as RRAM, FeFET, FTJ, device fabrication, electrical characterization, device modeling, and reliability. The lab emphasizes end-to-end research from device fabrication to AI hardware demonstration, with in-house fabrication facilities and advanced electrical characterization equipment. Students working on semiconductor devices can use ALD, sputtering, and basic photolithography equipment, along with Keithley 4200A systems and Keysight B1500 analyzers for characterization. Preferred applicants should have a degree in Electrical/Electronics Engineering, Computer Engineering, Computer Science, or a related field, and research experience during the master's program is preferred. The professor prefers direct PhD applicants rather than integrated MS–PhD applicants. Strong backgrounds in AI, device modeling, circuits, computer architecture, or semiconductor devices are especially relevant. Funding is available through tuition scholarships. Outstanding students may receive a 100% tuition scholarship. Applicants with TOEFL iBT ≥71, IELTS ≥5.5, or CEFR B2 (or equivalent) may be eligible for a 50% tuition scholarship, and the group may supplement the monthly research assistantship to cover the remaining tuition, creating effective full financial support. Interested candidates should email the professor with a CV, brief research summary, expected graduation date, and English test score if available. Early contact is encouraged. The post explicitly says not to inquire about postdoctoral positions.