goal is to design personalized and adaptive indoor soundscapes that reduce distraction, support concentration, and improve well-being, while ensuring that no speech content or private information is recorded. This project offers an exciting opportunity to work at the intersection of acoustic engineering, artificial intelligence, psychoacoustics, and human-centred design, with potential applications in offices, healthcare, education, and future hybrid workplaces.

Candidates with strong backgrounds in one or more of the following areas are encouraged to apply:

• Good background in acoustics, signal processing, audio engineering, or a related discipline
• Prior experience in audio signal processing, machine learning, deep learning, embedded/edge AI, psychoacoustics, or human–computer interaction would be highly valuable
• The student should be comfortable with programming in Python, working with audio data, conducting experiments with human participants, and analysing both objective acoustic measures and subjective user responses
• Strong analytical thinking, good communication skills, research independence, and an interest in applying AI to real-world acoustic and well-being challenges are essential

goal is to design personalized and adaptive indoor soundscapes that reduce distraction, support concentration, and improve well-being, while ensuring that no speech content or private information is recorded. This project offers an exciting opportunity to work at the intersection of acoustic engineering, artificial intelligence, psychoacoustics, and human-centred design, with potential applications in offices, healthcare, education, and future hybrid workplaces.

Candidates with strong backgrounds in one or more of the following areas are encouraged to apply:

• Good background in acoustics, signal processing, audio engineering, or a related discipline
• Prior experience in audio signal processing, machine learning, deep learning, embedded/edge AI, psychoacoustics, or human–computer interaction would be highly valuable
• The student should be comfortable with programming in Python, working with audio data, conducting experiments with human participants, and analysing both objective acoustic measures and subjective user responses
• Strong analytical thinking, good communication skills, research independence, and an interest in applying AI to real-world acoustic and well-being challenges are essential