Principal R&D Scientist

Onto Innovation•Milpitas, CA

1d•$160,000 - $240,000

About The Position

Onto Innovation is seeking a highly motivated X-Ray expert to conduct advanced research supporting next-generation metrology solutions for semiconductor manufacturing. The scientist will perform X-Ray experiments, collect and analyze measurement data, develop theoretical models, and create physics-based and machine learning algorithms for microelectronics and advanced-material characterization. The research will develop and optimize X-Ray metrology techniques, including X-Ray diffraction (XRD), X-Ray reflectivity (XRR), X-Ray fluorescence (XRF), and critical-dimension small-angle X-Ray scattering (CD-SAXS). CD-SAXS is a primary area of emphasis, with the goal of accurately and precisely characterizing the structure, composition, and dimensions of semiconductor structures, thin films, and advanced materials. The role operates at the intersection of experimental science, computational modeling, data analytics, and machine learning. It requires technical independence, attention to experimental detail, and effective communication of research results to technical stakeholders. The scientist will collaborate with product and software engineering teams to transfer research concepts into production-ready solutions.

Requirements

Ph.D. in physics, applied physics, materials science, chemical engineering, or a closely related technical field, with a strong academic background in X-Ray science.
Deep understanding of the physics and instrumentation of advanced X-Ray techniques, with hands-on data-analysis experience in CD-SAXS, XRD, XRR, or XRF.
Experience conducting X-Ray experiments at a synchrotron, national laboratory, or comparable advanced research facility.
Experience optimizing experimental methods for throughput, sensitivity, precision, and signal-to-noise performance.
Experience with rigorous electromagnetic modeling, scattering theory, computational physics, or related simulation techniques.
Familiarity with X-Ray hardware configurations and incorporating system non-idealities into theoretical simulations.
Experience developing analytical or numerical methods for inverse-problem solving, optimization, parameter estimation, signal processing, and statistical inference.
Familiarity with uncertainty quantification, error-budget development, Gauge R&R, measurement-system analysis, and metrology validation.
Demonstrated experience using Python, MATLAB, JMP, or comparable scientific-computing and statistical-analysis tools.
Experience developing machine learning or AI methods for scientific data analysis, physical-system modeling, parameter extraction, or inverse problems.
Excellent communication skills and ability to present technical materials to working-level peers and senior management, internally and externally.
Ability to work independently and collaborate effectively with multidisciplinary and geographically distributed stakeholders.
Ability to travel up to 25%.

Nice To Haves

Knowledge of semiconductor devices, thin films, nanoscale structures, microelectronics manufacturing, or advanced materials.
Evidence of research impact through publications, conference presentations, patents, technical reports, or successful technology transfer.

Responsibilities

Execute routine alignment and maintenance of X-Ray metrology equipment, and develop calibration methods and procedures to maintain measurement accuracy.
Coordinate and perform data collection on standard reference samples and engineering samples.
Conduct Gauge Repeatability and Reproducibility (Gauge R&R) testing, qualify tool stability, and quantify short- and long-term measurement precision.
Design and test measurement recipes and optimize collection strategies for throughput and signal-to-noise ratio.
Develop and refine physical models using rigorous electromagnetic methods to fit X-Ray data and solve inverse problems for parameters such as thickness, composition, critical dimensions, tilt, recess, shape factors, and local structural variations.
Develop and optimize machine learning and AI-based data analysis algorithms to accelerate data inversion and improve the robustness of microelectronics characterization.
Process datasets using statistical software and libraries such as Python, MATLAB, and JMP to identify process trends, anomalies, and correlations with reference techniques such as TEM, AFM, and CD-SEM.
Establish error budgets and uncertainty estimates to validate metrology-system limits of detection and quantification.
Present research findings and milestones to stakeholders within and outside Onto Innovation.
Prepare weekly work summaries, technical reports, white papers, and presentations describing metrology capability findings.
Deliver technical transfer packages describing data-analysis algorithm design and requirements to product and software engineering teams.
Work independently while collaborating with multidisciplinary and geographically distributed stakeholders.
Travel up to 25%.