Process Integ and Yield Eng PhD Intern Grade 029

Job Details: Job Description: As a Process Integration and Yield Engineering PhD Intern, you will contribute to the development and optimization of advanced semiconductor manufacturing processes. In this hands-on role, you will analyze defect data, conduct experiments, and enhance process integration flows to support yield improvement initiatives. Collaborating with cross-functional engineering teams, you will tackle technical challenges, optimize metrology strategies, and help refine manufacturing processes in high-volume production environments. Your contributions will play a pivotal role in advancing Intel's cutting-edge semiconductor technologies. Business Group Intel Foundry is a global leader in semiconductor manufacturing, focused on delivering innovative technologies that power the world's most advanced products. As part of this group, you'll join a team dedicated to optimizing manufacturing processes, driving quality improvements, and supporting Intel's mission to create world-changing technology. Together, we push the boundaries of innovation to enable efficiency and scalability in high-volume production environments. Key Responsibilities - Contribute to the development and refinement of module processes and integration flows for semiconductor manufacturing. - Analyze defect data, conduct experiments, and assist with risk assessments to enhance yield improvement initiatives. - Collaborate with cross-functional engineering teams to troubleshoot process flow issues and optimize metrology strategies. - Apply advanced data analysis techniques to improve process performance and production efficiency. - Participate in continuous improvement efforts focused on enhancing manufacturing quality and scalability in high-volume environments. - Engage in hands-on learning through innovative projects that align with Intel's business goals and prepare you for future career opportunities. Qualifications: You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum qualifications and are considered a plus factor in identifying top candidates. Experience listed below would be obtained through a combination of your schoolwork, classes, research, relevant previous job, and/or internship experiences.     Minimum Qualifications • Must be currently pursuing a PhD degree in C hemistry, Physics, Material Science, Chemical Engineering, Electrical Engineering, Mechanical Engineering, Computer Science or related STEM Degree. • Proficiency in data analysis tools and methods. Preferred Qualifications • Expertise in database structures, research methods, machine learning, analytics packages (i.e., JMP, MATLAB, Octave), scripting languages (i.e., Python, JSL, Perl, TCL), programming languages (i.e., SQL, C/C++) , or application design and planning (Figma, Visio). • Hands-on experience with semiconductor fabrication, process integration, or yield engineering.  • Knowledge of Statistical Process Control (SPC), Design of Experiments (DOE), or machine learning techniques.  • Knowledge of semiconductor device physics and manufacturing fundamentals.  • Experience with Transistor Device Structures and Device Physics. • Experience with Semiconductor materials, fabrication, and device physics. • Experience with Semiconductor Devices (transistor, diode, etc.) • Experience with microscopy or materials characterization techniques.  • Experience working in cleanroom, laboratory, or advanced manufacturing environments.  • Strong communication skills and ability to collaborate effectively across multidisciplinary teams.  • Strong analytical, problem-solving, and data interpretation skills. • Demonstrated ability to partner with stakeholders to streamline busin