... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
... quantification, etc.). * Support metrology process control for materials moving through the ... cycle time, and measurement uncertainty. * Collaborate closely with process engineering ...
Utilizing cyber risk quantification to reduce uncertainty around cyber risk and improve executive decision making. * Creating andfacilitatingtable-top exercises. * Delivering operational resilience ...
Utilizing cyber risk quantification to reduce uncertainty around cyber risk and improve executive decision making. * Creating andfacilitatingtable-top exercises. * Delivering operational resilience ...
Utilizing cyber risk quantification to reduce uncertainty around cyber risk and improve executive decision making. * Creating andfacilitatingtable-top exercises. * Delivering operational resilience ...
Utilizing cyber risk quantification to reduce uncertainty around cyber risk and improve executive decision making. * Creating andfacilitatingtable-top exercises. * Delivering operational resilience ...
Utilizing cyber risk quantification to reduce uncertainty around cyber risk and improve executive decision making. * Creating andfacilitatingtable-top exercises. * Delivering operational resilience ...
Utilizing cyber risk quantification to reduce uncertainty around cyber risk and improve executive decision making. * Creating andfacilitatingtable-top exercises. * Delivering operational resilience ...
Uncertainty Quantification information
What is Uncertainty Quantification?
Uncertainty Quantification (UQ) is the science of quantifying, managing, and reducing uncertainties in computational models and real-world systems. It involves identifying sources of uncertainty in data, model parameters, and algorithms, then using statistical and mathematical methods to assess their impact on model predictions. UQ is essential in fields like engineering, finance, and environmental science to ensure that predictions and decisions are robust and reliable. Practitioners use techniques such as sensitivity analysis, probabilistic modeling, and Monte Carlo simulations to quantify and analyze uncertainties.
What are some common challenges faced by professionals in Uncertainty Quantification when working on multidisciplinary teams?
Professionals in Uncertainty Quantification (UQ) often collaborate with experts from fields like engineering, data science, and physics. A common challenge is communicating complex statistical concepts in an accessible way to team members without a quantitative background. Additionally, integrating uncertainty models into existing workflows and ensuring that all stakeholders understand how uncertainty impacts decision-making can be demanding. Effective UQ professionals are proactive in facilitating clear communication and tailoring their approach to fit the needs of diverse teams.
What is the difference between Uncertainty Quantification vs Data Scientist?
| Aspect | Uncertainty Quantification | Data Scientist |
|---|---|---|
| Required credentials | Advanced degrees in engineering, mathematics, or statistics | Degree in computer science, statistics, or related fields |
| Work environment | Research labs, engineering firms, simulation-based industries | Tech companies, finance, healthcare, and marketing |
| Industry usage | Engineering, aerospace, manufacturing, scientific research | Business analytics, product development, predictive modeling |
Uncertainty Quantification focuses on assessing and reducing uncertainty in models and simulations, often requiring advanced mathematical skills. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles involve statistics and data analysis, Uncertainty Quantification is more specialized in modeling uncertainties in engineering and scientific contexts, whereas Data Scientists work across diverse industries with a broader focus on data-driven insights.
What are the key skills and qualifications needed to thrive as an Uncertainty Quantification Specialist, and why are they important?
To thrive as an Uncertainty Quantification Specialist, you need a strong background in applied mathematics, statistics, and computational modeling, often supported by an advanced degree in a quantitative field. Familiarity with programming languages such as Python or MATLAB, and experience with simulation tools and statistical analysis software, are typically required. Strong problem-solving skills, attention to detail, and effective communication help professionals convey complex concepts to interdisciplinary teams. These skills are crucial for accurately assessing risks, making data-driven decisions, and improving the reliability of models in engineering, finance, or scientific research.
What are popular job titles related to Uncertainty Quantification jobs in Texas? For Uncertainty Quantification jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Uncertainty Quantification jobs in Texas look for? The top searched job categories for Uncertainty Quantification jobs in Texas are:
Job description
Responsibilities
- Be a key member of the semiconductor metrology lab, supporting R&D and production manufacturing.
- Develop, qualify, and maintain measurement recipes for inline and offline metrology tools (e.g., thickness, roughness, composition, stress, defect quantification, etc.).
- Support metrology process control for materials moving through the production line, ensuring measurement accuracy, repeatability, and throughput.
- Analyze large and complex datasets to identify trends, process excursions, and root causes; communicate findings clearly to process engineering and operations teams.
- Define, track, and report key performance indicators (KPIs) related to metrology capabilities, tool utilization, cycle time, and measurement uncertainty.
- Collaborate closely with process engineering, manufacturing, quality, and equipment teams to support process development and yield improvement.
- Support tool qualifications, gauge R&R studies, and continuous improvement initiatives for measurement methodologies.
- Establish best practices for data integrity, documentation, and statistical analysis.
- Support technology transfers from development to high-volume manufacturing.
- Interface with equipment vendors to maintain and service all instruments.
- Mentor junior engineers and technicians; provide technical leadership within the metrology function.
Technical Skills
- Strong background in semiconductor metrology techniques such as optical, X-ray, electron-beam, and bulk/surface analysis methods (e.g., XRD, SEM, AFM, wafer level defect mapping and classification).
- Experience setting up, optimizing, and maintaining measurement recipes on commercial metrology platforms.
- Advanced data analysis skills, including statistical process control (SPC), design of experiments (DOE), and uncertainty analysis.
- Proficiency with data analysis tools and programming environments (e.g., Python, MATLAB, JMP).
- Understanding of semiconductor manufacturing flows and inline metrology integration.
- Familiarity with yield analysis, process control methodologies, and manufacturing metrics.
- Ability to translate complex measurement data into actionable insights for cross-functional stakeholders.
- Strong documentation, presentation, and technical communication skills.
Education
- Typically requires a minimum of 7 years of related experience with a Bachelor's degree; or 5 years and a Master's.degree or a Ph.D.w 3 years exp in Materials Science, Physics, Electrical Engineering, Chemical Engineering, or a closely related field.
Safety Requirements
All employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards.
Quality and Environmental Responsibilities
Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System.
Culture Commitment
Ensure adherence to company's values (ICARE) in all aspects of your position at Coherent Corp.:
Integrity - Create an Environment of Trust
Collaboration - Innovate Through the Sharing of Ideas
Accountability - Own the Process and the Outcome
Respect - Recognize the Value in Everyone
Enthusiasm - Find a Sense of Purpose in Work
Coherent Corp. is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
If you need assistance or an accommodation due to a disability, you may contact us at talentacquisition@coherent.com.
Note to recruiters and employment agencies: We will not pay for unsolicited resumes from recruiters and employment agencies unless we have a signed agreement and have required assistance, in writing, for a specific opening.