Scientist (Machine Learning, Hybrid)

Job summary

A motivated scientist is sought to work at the intersection of machine learning and audiological data, focusing on translating research insights into real-world applications for hearing care. The role involves developing machine-learning models to predict hearing aid outcomes and satisfaction using complex datasets.

Qualifications

• PhD in Applied Machine Learning, Mathematical Modeling, Computer Science, Data Science, Biostatistics, Social Data Science, or Computational Audiology.
• Early-career researcher, typically within ~5 years post-PhD.
• Experience with applied machine learning on real-world data.
• Strong programming, statistical, and data engineering skills, including familiarity with cloud-based platforms.
• Proven ability to translate analytical methods into operational algorithms.
• Evidence of research output appropriate to career stage (e.g., publications, software).

Responsibilities

• Develop machine-learning models for audiological applications.
• Collaborate with research, development, and commercial teams.
• Work with data structures between research data and cloud storage platforms.
• Support R&D with scientific documentation and demonstrators.
• Publish findings in peer-reviewed journals and present at international conferences.

Skills

• Proficiency in machine learning and data analysis.
• Strong collaboration and communication skills.
• Ability to work with large-scale datasets and translate insights into practical applications.

Education

• PhD in a relevant field.

Tools

• Machine learning frameworks, statistical software, cloud-based data platforms.