Internship “Deploying Large Language Model and Multi-Audio Models for Audio

at  Austrian Institute of Technology

As Austria’s largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time, climate change and digitalisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria’s leading research institution at the highest international level and to make a positive contribution to the economy and society.
Our Center for Digital Safety & Security located in Vienna invites applications for an internship. Our experts from the Center for Digital Safety & Security are developing state-of-the-art information and communication technologies to ensure that our systems are highly secure and reliable in the context of comprehensive digitalisation and global networking.
The research field Data Science within our Competence Unit “Data Science & Artificial Intelligence” is leading in applied research of highly innovative aspects for scalable Artificial Intelligence (AI) applications as well as data science consulting and solutions for informed decisions based on big, heterogeneous and real-time data under strict IT security and privacy conditions.

YOUR QUALIFICATIONS AS AN INGENIOUS PARTNER:

• You are a senior student, or already have your Bachelor’s degree, or are enrolled in your Master’s studies in the field of informatics / software engineering, electrical engineering or similar.
• Experience in developing Deep Learning Models for relevant Audio domain would be an advantage
• Knowledge about Audio Machine Learning and Large Language Model (LLM) is a plus
• Interest in the conception of scientific studies and application-oriented questions of the industry
• Interest to work in a multidisciplinary team and collaborate on different topics
• Good verbal and written English skills (team language is English)

Please refer the Job description for details