Research Associate in Design Analytics and Music Physiology
This is an exciting opportunity for a data scientist with strong musical sensibilities to play a key role in the development of computational tools for remodelling music expressivity to achieve specific cardiovascular (autonomic) aims. The objectives will be to design and implement techniques to morph expressive music parameters in ways that powerfully impact listener perception and physiology in targeted ways, to evaluate these strategies and their effectiveness, and to develop algorithms to analyse users’ design decisions to learn from their choices.
The work will be carried out in the context of the ERC project COSMOS (Computational Shaping and Modeling of Musical Structures), augmented by the Proof-of-Concept project HEART.FM (Maximizing the Therapeutic Potential of Music through Tailored Therapy with Physiological Feedback in Cardiovascular Disease), on citizen/data science approaches to studying music expressivity and on autonomic modulation through music. See https://doi.org/10.3389/fpsyg.2022.527539.
The remodelled expressions will be rendered synthetically or through the project’s reproducing piano. Effectiveness of the expression remodelling at achieving the physiological aims will be tested on listeners, for example, through the HEART.FM mobile app tracking their physiology whilst they listen to the remodelled music. Successful transformations will be integrated into CosmoNote ( https://cosmonote.ircam.fr), the web-based citizen science portal of COSMOS, or a sister web application for widespread public deployment. Collaborative designs may be explored.
The successful candidate will make major contributions to, and be involved in, all aspects of the computational modelling, interaction design, and software development; testing and validation, including on listeners (healthy volunteers or patients); and, development of algorithms for the design analytics, liaising with other research team members, and with collaborators across multiple domains, and be able to prioritise and organise their own work to deliver research results.
They should be highly motivated, and have strong communication skills and a good track record of scientific publication. Personal integrity, a strong work ethic, and a commitment to uphold the highest standards in research are essential attributes.
The project is hosted by the Department of Engineering in the Faculty of Natural, Mathematical & Engineering Sciences and the School of Biomedical Engineering & Imaging Sciences (BMEIS) in the Faculty of Life Sciences & Medicine (FoLSM) at King’s College London. KCL was ranked 6th nationally in the recent Research Excellence Framework exercise. FoLSM was ranked 1st and Engineering was ranked 12th for quality of research.
The research will take place in BMEIS at St Thomas’ Hospital and Becket House, on the south bank of the River Thames, overlooking the Houses of Parliament and Big Ben in London.
This post will be offered on a fixed-term contract for 12 months (renewable to 31 May 2025)
This is a full-time post
Key responsibilities and outcomes
• Designing and developing computational algorithms and sandbox environments to remodel musical expressivity with targeted physiological outcomes
• Evaluating and validating the proposed methodologies and assessing their effectiveness and potential for clinical translation
• Integrating the expression transformation tools into sandbox environments for the web in collaboration with other software programmer(s)
• Following the principles of good software design, development, and documentation practices
• Preparing high-quality manuscripts for publication, writing clearly about the computational techniques, outcomes, and design analytics
• Presenting key findings at scientific conferences and public engagement events
• Maintaining suitable performance levels for the software, following good software design, development, and documentation practices
• Demonstrate collaborative approach to research and software development
• Liaise directly with internal / external colleagues in an independent manner
• Use initiative, discretion, knowledge and experience in planning, coordination and problem-solving
• Demonstrate ownership of tasks and development of solutions to problems
• Maintain an awareness and observation of ethical rules and legislation governing the storage of projected data
• Maintain an awareness and observation of confidentiality agreements with collaborators and external organisations
• Maintain an awareness and observation of appropriate procedures for the disclosure and protection of inventions and other intellectual property generated as part of the post holder’s activities and other team members working within the project
• To attend regular project meetings and training courses for professional and personal development as required
Communication & Networking
• Develop and maintain effective working relationships with staff within the School as well as externally
• Regularly communicate information in a clear and precise way
Decision Making, Planning & Problem Solving
• Lead in decisions that have a significant impact on their own work, that of others and be party to collaborative decisions
• Manage own workload, prioritising these in order to achieve their objectives
• Communicate to management any difficulties associated with carrying out work tasks
• Resolve problems where the solution may not be immediately apparent and where there is a need to use judgement to achieve resolution
• Plan in advance for heavy workload
• Use own initiative and creativity to solve problems
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
Skills, knowledge, and experience
1. PhD in operations research, statistics, computer science, music computing, or a related field
2. Experience designing/adapting computational algorithms to solve problems with objectives and constraints
3. Strong musical sensibilities, adaptable, willingness to learn, motivated to work with real-world music and physiological data
4. Good knowledge of software design principles and code management on Git
5. Excellent written and oral communication skills
6. Track record of high-quality, peer-reviewed scientific publications
7. Ability to work with people from diverse backgrounds and specialties
1. Experience with music software and related file formats and protocols
2. Experience programming graphical user interfaces to alter music properties
3. Hands on experience working with sound and music
Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.