Semiconductor R&D Yield Analysis Engineer

Growing by reflection.

Huawei’s vision is a fully connected, intelligent world.

To achieve this, we work to inspire passion for basic research around the world.

Our combined passion drives development across the global innovation value chain.

Huawei has the largest Research and Development organization in the world with 96,000+ employees in research centers around the globe.

In the UK, we already have design centers in Cambridge, London, Edinburgh and Ipswich.

We continue to explore and define new research directions and new services.

We have expanded our collaborations with academic researchers; researched new network architectures, integration of communications and key enabling technologies; and developed the fundamental theories of these technologies.

We invite you to join us on this exciting journey and drive your career forward.

We are seeking a Semiconductor R&D yield analysis Engineer to support the development and optimization of next generation semiconductor photonic devices.

This role requires a deep understanding of III-V semiconductor photonics device physics and process, strong problem-solving skills, and a passion for continuous improvement.

You will work closely with cross-functional teams to transform large-scale experimental and fabrication data into actionable insights that contribute to improve R&D related design modelling, performance, process optimization and reliability.

The role offers an exciting opportunity to contribute to cutting-edge developments in semiconductor photonics and integrated optical technologies.

Analyse design simulations, semiconductor fabrication, and testing processes to identify performance characterisations, trends, correlations, and anomalies in performance.

Develop and apply statistical analysis and machine learning models to improve device performance, yield, and reliability.

Build automated data analysis tools and workflows using Python, R, or MATLAB.

Perform data-driven and conduct electrical and physical failure analysis specific to R&D yield loss.

Generate clear reports to support R&D engineering and management decision-making.

Collaborate with project stakeholders including design engineers, process engineers, test teams and project manager to understand data requirements, help optimize iterations.

Technology Integration: Stay current with industry trends and integrate new technologies and methodologies to improve R&D yield performance.

Proactively learning new software, algorithms, and techniques to stay competitive and improve work processes.

Interact with customers and collaborate closely with HQ to ensure effective communication, strong cross-functional collaboration, alignment on customer needs, and high levels of customer satisfaction.

This job description is only an outline of the tasks, responsibilities and outcomes required of the role.

The jobholder will carry out any other duties as may be reasonably required by his/her line manager.

The job description and personal specification may be reviewed on an ongoing basis in accordance with the changing needs of Huawei Research and Development UK Limited.

PhD in Physics, Photonics, Electrical Engineering, Semiconductor Engineering, Data Science, or a related field.

In-depth knowledge of III-V semiconductor optoelectronic device and laser physics

Strong programming skills in Python/R for data analysis and automation.

with machine learning frameworks such as Scikit-learn, TensorFlow, Pytorch or Keras.

with MATLAB for more advanced data analysis and simulations.

Knowledge of SQL to query databases for extracting relevant data. · Proficiency with statistical analysis methods such as regression analysis, hypothesis testing, and statistical process control.

Strong analytical and problem-solving skills with the ability to interpret complex datasets.

Flexible attitude to working hours.

Academic and/or Industry experience in III-V semiconductor optoelectronic device

In-depth knowledge and experience of fabricating process and testing of III-V optoelectronic devices and components

In-depth knowledge of device optical and electronic characterization techniques and ability to perform semiconductor failure analysis to identify root causes of defect and improve product quality.

with big data tools such as Hadoop or Spark.

developing automated data pipelines and scalable analytics workflows.

Multilingual skills are an advantage, along with the flexibility to work across different time zones.