About this role

We are looking for a graduate student to join our Camera Hardware Process Engineering team in Herzliya. The team defines the process for camera and sensor modules, including the assembly flow, machines, and materials, from early incubation through bring-up and production readiness. As an intern, you will support failure analysis, contribute to incubation projects in process development, and take part in bringing up new process setups. The environment is collaborative and hands-on. You will work with experienced engineers on real products.

Failure analysis (FA) support:
Prepare cross-sections and run inspections by electron microscopy (mainly SEM).
Measure surface roughness and gloss.
Analyze data for commonality checks across builds, lots, machines, and materials.
Summarize findings and present them to the team.

Incubation projects:
Support process development experiments on new materials, processes, and equipment.
Plan and run DOEs, and document the results.
Help evaluate process windows and risks.

Process set-up and bring-up:
Work hands-on with new tools and fixtures: install, calibrate, and qualify them.
Run builds, collect data, and troubleshoot.
Document process flows, set-up procedures, and lessons learned.

Minimum Qualifications

Currently enrolled in an M.Sc. or Ph.D. program in Materials Science, Mechanical, Electrical, or Chemical Engineering, Physics, or a related field.
Proficient verbal and written English.
Hands-on lab skills and comfort working with equipment and tooling.
Strong data analysis skills, with proficiency in Python, JMP, MATLAB, or Excel.
Analytical, detail-oriented approach to root-cause investigation.
Clear written and verbal communication, and the ability to work with cross-functional teams.
Self-directed, curious, and eager to learn within an experienced team.

Preferred Qualifications

Experience with SEM, FIB, or cross-section sample preparation.
Experience with surface metrology (roughness/gloss measurement).
Knowledge of electronics packaging, optics, adhesives, or precision assembly.
Familiarity with statistics, DOE, root-cause methods (8D, 5-Why).