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Moises · 4 hours ago

PhD Research Internships – Music Generation / Source Separation and Enhancement / Music Information Retrieval

United States

Internship

Remote

Intern

Moises is a fast-growing startup in the Music Tech space, building next-generation tools that empower musicians and producers. They are looking for motivated research interns to join their team, focusing on audio source separation, music information retrieval, and music generation.

Artificial Intelligence (AI)Machine LearningMusic

Responsibilities

Research and prototype models for isolating instruments, vocals, and other musical components

Explore audio enhancement approaches such as denoising, dereverberation, and quality restoration

Work with large audio datasets, model training pipelines, and evaluation metrics

Collaborate with engineers and audio specialists to integrate models into music‑production‑oriented workflows

Develop algorithms for tasks such as beat tracking, chord recognition, structural segmentation or tagging

Experiment with machine learning and signal processing approaches to extract insights that support musicians and producers

Work with the team to integrate MIR features into creative and production‑oriented tools

Research and prototype generative models for conditional music generation

Experiment with diffusion and/or autoregressive models, and embedding and/or token‑based audio/music representations

Collaborate with the team to integrate generation features into tools intended for musicians and producers

Qualification

Audio signal processingMachine learningDeep learning frameworksSource separation techniquesMusic Information RetrievalGenerative modelingMusical intuitionMusic theory knowledgePersonal music production experience

Required

PhD candidates currently enrolled in relevant programs

Exceptional MSc candidates with strong research experience may also be considered