- Location
- AP-TW-Hsinchu (EL), Taiwan
- Type
- Full-time
- Department
- Education
- Seniority
- Senior
- Experience
- 2+ years
- Education
- PhD
- Source
- Workday
Description
Are you looking to power the next leap in the exciting world of advanced electronics? Do you want to help solve problems that drive success in the rapidly evolving technology and connectivity landscape? Then bring your problem-solving, passion, and creativity to help us power the next leap in electronics.
At Qnity, we’re more than a global leader in materials and solutions for advanced electronics and high-tech industries – we’re a tight-knit team that is motivated by new possibilities, and always up for a challenge. All our dedicated teams contribute to making cutting-edge technology possible. We value forward-thinking challengers, boundary-pushers, and diverse perspectives across all our departments, because we know we play a critical role in the world enabling faster progress for all. Learn how you can start or jumpstart your career with us.
Key Responsibilities
Qnity is accepting applications for a position as a Data Scientist – CFD & Multiphysics Modeling. This position will be based at Qnity’s Hsinchu Site I, Taiwan. This is an exciting opportunity to join a growing Data Science team that plays a vital and dynamic role in Qnity’s R&D organization.
A strong candidate will have expertise in data science practices such as data cleaning, regression, machine learning, deep learning, large language models, and computer vision. The applicant should have fluent coding skills in Python, with the ability to prepare data for analysis, build models, create descriptive plots and reports, and understand deep learning models, including large language models and computer vision models.
Experience or interest in CFD-enabled and multiphysics modeling for wet-chemistry and deposition processes would be valuable for this role, particularly in semiconductor and electronics applications. The candidate will work with R&D, process engineering, and data engineering teams to translate experimental, modeling, and simulation insights into actionable process, formulation, and equipment recommendations. Beyond technical skills, the role requires an organized problem-solver who can structure complex problems into logical steps, communicate methods and results clearly to business and technical stakeholders, and collaborate across functions to deliver practical solutions.
Qualifications
A PhD degree, or a Master’s degree with at least 2 years of relevant experience, in a science or engineering technical field.
Strong coding skills in Python, including data preparation, regression, model development, visualization, and reporting.
Formal education in statistics, including regression, hypothesis testing, and experimental data analysis.
Strong knowledge of machine learning and deep learning techniques, with exposure to large language models, vision-language models, computer vision models, and AI workflow orchestration.
Experience applying data science to solve business, engineering, or scientific problems, with the ability to convert ambiguous technical questions into structured analytical workflows.
Basic competency with SQL, MongoDB or similar database queries, and visualization prototyping.
Self-learning mindset and intellectual curiosity to keep abreast of advances in data science, grow technical expertise, and refine understanding of internal business operations over time.
Effective interpersonal skills for communicating technical concepts to non-experts, collaborating with team members, and presenting analysis results to internal clients.
Preferred experience with COMSOL Multiphysics or other CFD / multiphysics tools for modeling fluid flow, species transport, electrochemical reactions, current distribution, or deposition processes.
Preferred knowledge of transport phenomena, electrochemical kinetics, electroplating, thin-film deposition, or wet-chemistry processes relevant to semiconductor or electronics applications.
Preferred experience validating simulation results against experimental or process data, such as electrochemical measurements, thickness profiles, metrology data, or other process characterization results.
Exposure to simulation automation, model calibration, design of experiments, surrogate modeling, or physics-informed machine learning is preferred.
Experience with cloud computing or scalable computing environments, such as Microsoft Azure, for data science or simulation workflows.
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Qnity is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability or any other protected class. If you need a reasonable accommodation to search or apply for a position, please visit our Accessibility Page for Contact Information.
Qnity offers a comprehensive pay and benefits package. To learn more visit the Compensation and Benefits page.
We use Artificial Intelligence (AI) to enhance our recruitment process.
