Research Associate in Machine Learning for Hearing - Sheffield, United Kingdom - University of Sheffield

University of Sheffield

Verified Company

Sheffield, United Kingdom

2 weeks ago

Posted by:

Tom O´Connor

beBee Recruiter

Description

We welcome applicants with Python software development experience and a PhD in Speech and Hearing Technology, Machine Learning or a related area.

Your role will involve authoring open-source tools and baseline systems for use in future Clarity Challenge rounds.

You will then be working with the project team and members of the international research community to coordinate these challenges.

You will also have the opportunity for conducting novel research in speech intelligibility enhancement and speech intelligibility prediction.

The role will place you at the centre of a rapidly growing community of researchers who are using machine learning approaches to improve hearing aid performance.

The Department of Computer Science was established in 1982 and has since attained an international reputation for its research and teaching.

In the 2021 Research Excellence Framework (REF) exercise, 99% of our research was rated as either 'world leading' or 'internationally excellent'.

Much of our research spans the boundaries between engineering, medicine and the life sciences.

Research in the Department is organised into a number of groups:

Machine learning, Algorithms, Complex systems modelling, Natural language processing, Speech and hearing, Organisations, information and knowledge (OAK), Verification and testing, Visual computing, and Security of Advanced Systems.

We attract substantial external funding from UK Research Councils, the European Union and industry. Our record for

We're one of the best not-for-profit organisations to work for in the UK.

The University's Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect.

We believe diversity in all its forms delivers greater impact through research, teaching and student experience.