This is an exciting opportunity for a data scientist with experience in cardiovascular signal processing and interests in music to play a key role developing computational techniques to optimise music expressivity to achieve specific cardiovascular aims. The objectives will be to design and implement computational techniques to infer causal relationships between expressive music parameters and surface or intracardiac measurements; and, to re-model the music parameters to achieve targeted physiological responses. The remodelled musical expressions will be rendered through a reproducing piano. The effectiveness of the strategies will be validated through physiological measures.
The work will be carried out in the context of the ERC project COSMOS (Computational Shaping and Modeling of Musical Structures, https://cosmos.isd.kcl.ac.uk
), assisted by tools created in COSMOS and in the Proof-of-Concept project HEART.FM (Maximizing the Therapeutic Potential of Music through Tailored Therapy with Physiological Feedback in Cardiovascular Disease, https://heartfm.kcl.ac.uk
), on citizen/data science approaches to studying music expressivity and on autonomic modulation through music. Strategies for music re-shaping will be integrated into a web-based citizen science portal in collaboration with the CosmoNote ( https://cosmonote.isd.kcl.ac.uk
) software engineer.
The successful candidate will make major contributions to, and be involved in, all aspects of the computational modelling, algorithm design, and software development, testing, and validation, including on listeners (healthy volunteers or patients); liaising with research team members, and with collaborators across multiple domains, and be able to prioritise and organise their own work to deliver research results.
The successful candidate will have a PhD in data science or a closely-related field, with experience in cardiovascular signal processing, and demonstrated facility with statistical and optimisation techniques. Having sound musical judgement is a plus. They should be highly motivated and keep abreast of research developments, particularly in cardiovascular science. They should have strong written and oral 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 Cardiovascular Imaging in the School of Biomedical Engineering & Imaging Sciences (BMEIS) in the Faculty of Life Sciences & Medicine (FoLSM), and by the Department of Engineering in the Faculty of Natural, Mathematical & Engineering Sciences, 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, which is embedded in 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 until 31 May 2025 (or up to 30 Nov 2025, pending a 6-month no-cost extension approval)
This is a full-time post