Postdoc: Data-Driven X-ray Nanoimaging for Chip Metrology

1000scholars; Villigen; On-site; CHF 85,000 - 100,000; Full time

Job summary

EPFL seeks a Postdoctoral Researcher in Data-driven X-ray Nanoimaging for Semiconductor Metrology at Villigen, Switzerland. You will develop acquisition and reconstruction frameworks using known device geometry and design information to detect defects from the fewest X-ray measurements, with demonstrations at synchrotron facilities.

The role focuses on algorithm development and processing thousands of diffraction patterns, leading independent research directions, and collaborating with

Qualifications

• PhD in physics, engineering, computer science, or related field.
• Strong scientific programming in Python and experience with GPU processing of large-scale datasets.
• Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related modality.
• Excellent written and oral communication skills in English.

Responsibilities

• Develop an acquisition and reconstruction framework using prior information to detect deeply buried defects from minimal X-ray measurements.
• Reconstruct projections from thousands of diffraction patterns and perform volume reconstruction from many angles.
• Extend and integrate the established reconstruction pipeline with new data acquisition methods.
• Collaborate on synchrotron experiments at cSAXS beamline and other facilities.

Skills

Python programming

GPU processing

Inverse problems

3D reconstruction

Data-driven imaging

English communication

Education

PhD in physics, engineering, computer science, or related field

Tools

GPU acceleration

Job description

EPFL seeks a Postdoctoral Researcher in Data-driven X-ray Nanoimaging for Semiconductor Metrology at Villigen, Switzerland. You will develop acquisition and reconstruction frameworks using known device geometry and design information to detect defects from the fewest X-ray measurements, with demonstrations at synchrotron facilities.

The role focuses on algorithm development and processing thousands of diffraction patterns, leading independent research directions, and collaborating with