Intern - Advanced DRAM Cell & Device Technology

Micron Technology · Boise, ID - Main Site

onsiteinternshipFresher / Intern

posted 16h

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron's Boise R&D site, the DRAM Technology Development organization drives innovation in next-generation memory solutions. The team develops advanced DRAM cell architectures, access devices, materials systems, and integration technologies that enable future scaling, improved performance, enhanced reliability, and manufacturing readiness. Engineers work across device, materials, process integration, modeling, design, and product engineering teams to bring groundbreaking memory technologies from concept to production. As an intern in the Advanced DRAM Device & Cell Technology team, you will contribute to the development and characterization of future DRAM cell and access device technologies through experimental studies, data analysis, and collaboration with multidisciplinary engineering teams. This position combines semiconductor device physics, materials engineering, silicon experimentation, electrical characterization, and data-driven decision making to improve cell performance, density, retention, reliability, and manufacturability. The successful candidate will collaborate with multi-functional teams to evaluate novel materials, device architectures, and integration schemes supporting future memory technology development. Responsibilities Support the evaluation of DRAM access devices, capacitors, and cell stack elements through characterization, data analysis, and assessment of new device architectures, materials systems, and integration schemes. Design and implement silicon experiments; perform electrical, physical, and materials characterization along with statistical analysis to find opportunities for device, process, and design improvements. Analyze device- and array-level behavior including sensing margins, activation characteristics, disturb mechanisms, retention performance, leakage behavior, and read/write operation interactions. Collaborate with modeling, design, process integration, and manufacturing teams to understand device behavior, support technology optimization, and contribute to technology development activities. Apply AI-Assisted and Generative AI tools, where appropriate, to enhance data analysis, workflow efficiency, and technical decision-making. Minimum Qualifications Currently pursuing an M.S. or Ph.D. in Electrical Engineering, Materials Science, Applied Physics, Chemical Engineering, or a related technical field. Cannot graduate prior to September 2027. Demonstrated understanding of semiconductor fundamentals, including device physics, materials science, characterization techniques, and concepts relevant to advanced memory technologies. Experience with electrical characterization, device testing, statistical analysis, and interpretation of experimental or simulation data sets. Familiarity with DRAM operational concepts, including activation, sensing, retention, and disturb mechanisms. Proficiency with data analysis and scripting tools such as Python, MATLAB, JMP, or similar platforms, along with familiarity with AI-assisted engineering and data analysis tools. Preferred Qualifications Experience in DRAM or NAND device development, characterization, or technology research. Hands-on experience with semiconductor materials characterization, process development, thin film engineering, interface engineering, TCAD simulation, and/or advanced memory technology research. Knowledge of semiconductor fabrication processes, advanced BEOL integration, reliability mechanisms, and device variation analysis. Experience conducting independent research projects and effectively communicating technical results to diverse audiences. Experience using AI, Large Language Models (LLMs), AI-enabled analytics, or AI-support