Job Summary & ResponsibilitiesPosition SummaryWe are seeking a highly motivated X-Ray expert to conduct advanced X-Ray research supporting the development of 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 focus on developing and optimizing advanced 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 will be a primary area of emphasis, with the goal of enabling accurate and precise structural, compositional, and dimensional characterization of semiconductor structures, thin films, and advanced materials.
The successful candidate will work at the intersection of experimental science, computational modeling, data analytics, and machine learning. This position requires strong technical independence, attention to experimental details, and the ability to communicate research results effectively to technical stakeholders.
Key ResponsibilitiesData collection and Hardware management- Execute routine alignment and maintenance of X-Ray metrology equipment, 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 measurement short- and long-term precision.
- Design and test measurement recipes and optimize collection strategies for high throughput, and signal-to-noise ratio.
Data Analysis and Algorithm Development- Develop and refine physical models with rigorous electromagnetic methods to fit X-Ray data, solve inverse- problem to extract thickness, composition, critical dimensions (CD), tilt, recess, shape factors, local structural variations, and other parameters of interest for microelectronics devices.
- Develop and optimize Machine Learning and AI-based data analysis algorithms to accelerate data inversion and enhance the robustness of microelectronics characterization.
- Process datasets using statistical software/libraries (e.g., Python, MATLAB, JMP) to identify process trends, anomalies, and correlation with reference techniques (TEM, AFM, CD-SEM etc.).
- Establish error budgets and uncertainty estimation to validate the limits of detection and quantification of the metrology system.
Documentation and Stakeholder Collaboration- Meet and present research findings and milestones to stakeholders within and outside Onto Innovation.
- Generate weekly work summaries and detailed technical reports, white papers and presentations summarizing metrology capability findings.
- Deliver technical transfer packages with data analysis algorithm design and requirements to product and software engineering teams to transition research concepts into production-ready solutions.
QualificationsQualifications- 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 experience in data analysis for 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.
- Knowledge of semiconductor devices, thin films, nanoscale structures, microelectronics manufacturing, or advanced materials is a plus.
- Evidence of research impact through publications, conference presentations, patents, technical reports, or successful technology transfer.
- Excellent communication skills and ability to present technical materials both to working-level peers and to senior management internally and externally.
- Ability to work independently while collaborating effectively with multidisciplinary and geographically distributed stakeholders.
- Ability to travel up to 25%.
Success AttributesThe ideal candidate will demonstrate:
- A rigorous, data-driven approach to technical problem solving.
- Strong scientific curiosity and self-motivation, and persistence when working through complex experiments, iterative modeling, and detailed data validation.
- Attention to data quality, reproducibility, uncertainty, and documentation.
- Ability to integrate experimental observations, physical understanding, and computational methods.
- Willingness to perform both innovative algorithm development and conventional data analysis methods required to achieve optimal measurement performance.
- Clear communication and effective collaboration with research, engineering, and business stakeholders.
Compensation & Growth• Base Salary Range:
$160,000.00 - $240,000.00, offered in good faith and based on experience, location, and qualifications.
- Additional Rewards: Annual bonus opportunities and potential long-term incentives tied to both company and individual success.
