Practical Trainee - Hearing Device Data & Machine Learning
Practical Trainee - Hearing Device Data & Machine Learning
Practical Trainee - Hearing Device Data & Machine Learning
Practical Trainee - Hearing Device Data & Machine Learning
Sonova Group
Medizintechnik
Stäfa
- Art der Anstellung: Vollzeit
- 104.500 CHF – 126.500 CHF (von XING geschätzt)
- Vor Ort
- Zu den Ersten gehören
Practical Trainee - Hearing Device Data & Machine Learning
Über diesen Job
Who we are
At Sonova, we envision a world where everyone can enjoy the delight of hearing. This vision inspires us and fuels our commitment to developing innovative solutions that improve hearing health and human connection - from personal audio devices and wireless communication systems to hearing aids and cochlear implants. We're dedicated to providing outstanding customer experiences through our global audiological care services, ensuring that everyone has the opportunity to engage fully with the world around them.
Guided by a culture of continuous improvement that fosters resilience and self-motivation, our team is united by a shared commitment to excellence and a deep sense of pride in our work, each of us playing a vital role in creating meaningful change,
Here you’ll find a diverse range of opportunities that span both consumer and medical solutions and the freedom to shape your career while making an impact on the lives of others. Join us in our mission to create a more connected world, where every voice is heard and every story matters.
Staefa, Switzerland
Practical Trainee - Hearing Device Data & Machine Learning
Purpose of the job:
As a Practical Trainee, you will develop an auditory attention model using EEG data that is already being collected. This model will be a key component for a non-clinical study that is currently in preparation. The study aims to demonstrate the performance of a non-invasive listening intention model developed within the Darling project. This non-invasive listening intention technology is planned for integration into products following the Axl generation.
Tasks:
- Performing a sanity check on the EEG data and their associated labels.
- Conducting research to identify the optimal set of features for model training.
- Training and validating an Auditory Attention Decoding (AAD) model.
- Validating the LI labels through the application of the trained AAD model.
- Producing comprehensive documentation of the methodology, process, and results.
Your profile:
- A strong command of machine learning techniques, with a preference for experience in deep learning.
- Experience with EEG data and neural signal processing.
- Strong mathematical and programming skills to handle large datasets.
- Well-developed analytical and critical thinking abilities.
- A demonstrated aptitude for effective teamwork and collaboration.
- Excellent organizational skills, particularly in producing clear, maintainable code and thorough documentation.
- Ideally, background in hearing devices or auditory systems.
We can offer you a new challenge, with interesting tasks and much more – including an open corporate culture, flat hierarchies, support for further training and development, opportunities to take on responsibility, an excellent range of foods, sports and cultural facilities, attractive employment conditions, and flexible working time models in various roles.
Sonova is an equal opportunity employer.
We team up. We grow talent. We collaborate with people of diverse backgrounds to win with the best team in the market place. We guarantee every person equal treatment in regard to employment and opportunity for employment, regardless of a candidate’s ethnic or national origin, religion, sexual orientation or marital status, gender, genetic identity, age, disability or any other legally protected status.
Gehalts-Prognose
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Gesamtbewertung
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Unternehmenskultur
Unternehmenskultur
337 Mitarbeitende haben abgestimmt: Sie bewerten die Unternehmenskultur bei Sonova Group als ausgeglichen zwischen traditionell und modern.Dies stimmt ungefähr mit dem Branchen-Durchschnitt überein.