OPPORTUNITIES:

Harmonic Analysis Research Assistant (Paid, Remote)
SheetMuse — Music AI Platform

SheetMuse is developing advanced music-AI technology to help musicians learn songs faster through precise harmonic analysis, intelligent audio processing, and machine learning.

We are seeking a small number of highly capable music students to assist in building a large-scale chord annotation dataset that will support next-generation music intelligence systems.

This role is analytical, ear-driven work — ideal for musicians with strong theory training who enjoy deep listening.

About SheetMuse

SheetMuse sits at the intersection of music, signal processing, and artificial intelligence. Our mission is to build tools that meaningfully improve how musicians practise, perform, and understand repertoire.

You will be contributing directly to a foundational dataset powering these systems.

What You’ll Do

  • Label chords with accurate timing while listening to recorded music

  • Identify harmonic movement including substitutions, extensions, modal interchange, and altered chords

  • Resolve ambiguous passages using musical judgement

  • Follow structured annotation standards

  • Help refine internal harmonic guidelines

Who This Is For

Students with strong harmonic fluency, particularly in:

  • Jazz studies

  • Composition

  • Musicology

  • Contemporary performance

  • Advanced theory pathways

Honours, Masters, and PhD students are strongly encouraged to apply.

Essential Requirements

  • Excellent working knowledge of harmony

  • Ability to recognise chords by ear

  • Strong attention to detail

  • Reliable and self-directed

Nice to Have

  • Transcription experience

  • DAW familiarity

  • Interest in music technology

  • Exposure to music information retrieval

Role Details

  • Paid: $30–50 AUD per hour depending on experience

  • Remote with flexible hours

  • Initial commitment: ~5–10 hours per week

  • Ongoing opportunities as the dataset expands

Exceptional contributors may be invited into longer-term research collaborations.

Why This Role Matters

High-quality harmonic datasets are rare. Your work will directly support technology designed to serve musicians globally.

Where appropriate, outstanding contributors may be recognised in future research outputs.

Application Process

Please email the following to matt@stepincto.com

  • Short summary of musical background

  • Degree program and year level

  • Description of harmony training

  • Any transcription or analytical work

Shortlisted applicants will complete a brief paid harmonic listening exercise.

Subject line: Harmonic Analysis Application