Location: | Nottingham |
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Salary: | £31,637 to £46,735 per annum, depending on skills and experience (minimum £35,116 with relevant PhD). Salary progression beyond this scale is subject to performance. |
Hours: | Part Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 22nd May 2025 |
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Closes: | 4th June 2025 |
Job Ref: | SCI152325 |
Applications are invited for the above Research Associate/Fellow post based at the University of Nottingham working with Professor Craig Vear on his project Digital Scores – investigating the technological transformation of the music score (DigiScore).
DigiScore is funded by a €2Million ERC-funded Consolidator grant (2021-2026). The project will work in partnership with Monash University (Australia), Concordia University (Canada), University California Santa Barbara (US), and the Central Conservatory of Music, Beijing (China). The post will be based at UoN and may involve international travel. The core aims of the research project are to determine scientific knowledge of how digital scores (Vear 2019) stimulate new creative opportunities and experiences within a range of music practices and to build a scientific study of inclusive digital musicianship through the transformative potential of the digital score.
The Digiscore project is seeking applications for a Post-Doctoral Research Associate/ Fellow in mixed methods research. This 1-year position will work with the PI and focus on a series of digital score research experiments investigating human-AI/ human-robot interaction. A particular focus is using mixed-method approaches to understand human-centred musical values such as ‘togetherness’ and this will involve designing and developing novel mixed-method experiments through a range of discreet, but related experiments with musicians.
We seek an experienced researcher who can be accountable for the design, delivery and quality of mixed-method research in the DigiScore project, with measurable outcomes. The Research Associate/Fellow will be a human computer interaction (HCI) specialist in qualitative (interview) data collection, analysis, and sensemaking. They should also have a broad understanding of quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required and there is an expectation to work independently on project specific and self-defined tasks and goals. The post holder will be experienced in research, which is reflected by a growing reputation in this field of research.
A suitable candidate will have the following qualities:
We welcome applications from everyone and value the varied perspectives and experiences that a diverse team can bring. We are proud to have an Athena Swan Bronze Award recognising good practice towards the advancement of gender equality in our school.
Our school uses anonymised recruitment for shortlisting, where we cannot see any personal data in your application, until shortlisting has been completed (you will apply by answering criteria-based questions relating to the person specification, rather than submitting a CV). We welcome applications from everyone, regardless of the categories you put yourself in.
This post will be offered on a fixed-term contract until 30 June 2026. Hours of work are part time, 29 hours per week.
Informal enquiries may be addressed to Prof Craig Vear at craig.vear@nottingham.ac.uk . Please note that applications sent directly to this email address will not be accepted.
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