Driven by the passion to improve the quality of people’s lives, WS Audiology continues to grow as the market leader in the hearing aid industry. With our commitment to increase penetration in an underserved hearing care market, we want to accelerate our business transformation to reach more people, more effectively.

As an R&D Intern - HW EAD, you will work on developing and implementing scientific machine learning models to solve partial differential equations, specifically for acoustic problems. You will conduct reviews of recently developed models and contribute to the analysis and refinement of these approaches. Additionally, you will be expected to publish the results obtained during your internship, contributing to the advancement of research in this field.

What you will do

• Work on the scientific machine learning model to solve partial differential equations
• Implement machine learning models for acoustic problems and contribute to the publication of results
• Conduct reviews on the recent developed scientific machine learning model

What you bring

Experience

• Undergraduate degree in Computer Science/Acoustics/Engineering
• High degree of independence and problem-solving skills
• Experience in machine learning model
• Strong coding abilities in Python and a popular deep learning framework such as Pytorch are essential
• Experience with acoustic background or solving PDEs is a plus

Who we are

At WS Audiology, we provide innovative hearing aids and hearing health services.

Together with our 12,000 colleagues in 130 countries, we invite you to help unlock human potential by bringing back hearing for millions of people around the world.

With us, you will become part of a truly global company where we care for one another, welcome diversity and celebrate our successes.

Sounds wonderful? We can't wait to hear from you.

WS Audiology is an equal-opportunity employer and committed to creating an inclusive employee experience for all. Regardless of race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status we firmly believe that our work is at its best when everyone feels free to be their most authentic self.