NOKIA is hiring: IC Package Design Researcher in New Providence

You will realize next-generation packaging solutions by identifying, integrating, and validating novel materials. It is a highly cross‑functional role, engaging RF/EM, mechanical/thermal, optical integration, reliability, supplier, and manufacturing teams. The ideal candidate brings a strong materials science and packaging background, hands‑on process know‑how, and a data‑driven approach to reliability‑by‑design.

Responsibilities

• Identify, integrate, and qualify novel materials into advanced microelectronics packages (e.g., dielectrics, interconnects, adhesives, TIMs, etc.).


• Drive package and test fixture design from architecture planning to CAD generation to system level validation, including mechanical, thermal, electrical, and optical design and accelerated reliability testing.


• Plan and execute material and package characterization and failure analysis.


• Collaborate with OSATs, Foundries, and material suppliers to validate new process flows and materials and identify and resolve failure mechanisms.


• Build data‑backed acceptance criteria for novel materials and correlate lab measurements with modeling results to inform design trade‑offs.

Qualifications

• M.S. or Ph.D. in Materials Science/Engineering, Mechanical Engineering, Electrical Engineering, Physics, Chemistry or a related field, with 5+ years in microelectronics packaging.


• Hands‑on experience with at least some of the following tools for package and system design (e.g., Cadence Allegro, Xpedition, Altium) and mechanical/thermal/EM simulation (e.g. Creo/Solidworks, Ansys Mechanical, FloTHERM/Icepak, HFSS, CST).


• Proficiency in characterization methods and failure analysis (Radiography, RF S‑parameters, optical insertion loss, DMA/TMA, SEM, AFM, etc.)


• Experience with wafer‑level and substrate fabrication processes and the ability to identify and de‑risk new processes.


• Strong cross‑functional collaboration and communication skills, with the ability to translate complex experimental data into clear design and process recommendations for both technical and non‑technical stakeholders.