My Sheet Music Transcriptions is at the forefront of sheet music and digital music notation services. While we believe music is a human phenomenon, we are committed to creating solutions that not only advance the field of music technology but also support and enhance the creative process of musicians and composers worldwide.
Job Description: We seek a Music Informatics Researcher with a background in symbolic music analysis and web app development. This role is crucial for advancing our research and product development projects that require a deep understanding of symbolic music data and web app deployment. The successful candidate will be instrumental in developing algorithms and web applications that cater to the analysis, generation, and interaction with symbolic music representations, alongside exploring innovative ways to transcribe and interact with music scores.
The goal? To enhance user experience, client lifetime value, and internal transcription and catalog workflow and management.
Key Responsibilities: Conduct research and development in music information retrieval with a focus on symbolic music data.
Design, implement, and evaluate algorithms for the analysis and generation of symbolic music representations.
Develop web-based applications to showcase and deploy symbolic music analysis and generation technologies.
Collaborate with cross-functional teams to integrate symbolic music technologies into user-friendly web applications.
Optional but advantageous: Contribute to projects involving music transcription from audio to symbolic representations, enhancing our capabilities in bridging different music data domains.
Maintain awareness of the latest advancements in symbolic music analysis, MIR, and web app development technologies.
Qualifications: PhD or Master's degree in Music Technology, Computer Science, Electrical Engineering, or related field, with a significant focus on symbolic music analysis and MIR.
Demonstrated experience in symbolic music analysis, including working with music scores and notation systems.
Proficiency in deploying web applications with a focus on showcasing music technology research (e.g., AWS, GCP).
Familiarity with music transcription techniques and tools is a plus, but not required.
Preferred Skills: Direct experience with music transcription projects and tools.
Knowledge of music theory, especially as it applies to music notation and score analysis.
Experience in machine learning and deep learning applied to symbolic music data.
Required Documents: Please submit your application, including a cover letter, CV, and a portfolio of projects demonstrating your experience with symbolic music analysis and web app development.
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