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Post-doctoral Research Fellow (Transforming Collections)

University Of The Arts London

Location: London
Salary: £39,275 to £47,120
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 15th November 2021
Closes: 3rd January 2022
Job Ref: 7473
 

We are seeking a Post-doctoral Research Fellow (PDRF) with experience designing and building Machine Learning (ML) systems for end users to work on the 3-year research project funded by the AHRC's Towards a National Collection programme, Transforming Collections: Reimagining Art, Nation and Heritage.

As PDRF, you will report to Co-Investigators based at UAL’s Creative Computing Institute (CCI), working towards the design and development of Machine Learning (ML) systems for end-users through interaction with partners from 15 collections. You will collaborate with Co-Investigators across other strands of the project in order to synthesise outcomes and support the design and delivery of participatory workshops/seminars with Project Partners, Collaborating Organisations and diverse stakeholders, integrating findings from these workshops into the design of new tools. You will have responsibility for developing and maintaining ML software and interfaces using Git, and academic reporting (e.g. conference/symposium papers and journal articles).

You will participate in regular project team meetings and a peer support network of the project’s researchers, developing interdisciplinary research expertise and develop skills and experience in collaborative, ethical and participatory workshop design and delivery. You will present and/or publish case studies in progress through the local, national and international spaces and networks generated by the project.

Why choose us? 

Transforming Collections is a £3m 3-year ‘Discovery Project’ funded as part of the major UKRI / AHRC programme, Towards a National Collection. Led by UAL’s Decolonising Arts Institute (DeAI) in collaboration with CCI, we will work closely with Tate as our Independent Research Organisation partner, and a further 14 Project Partners and Collaborating Organisations. Transforming Collections aims to enable cross-search of collections, surface patterns of bias, uncover hidden connections, and open up new interpretative frames and ‘potential histories’ (Azoulay, 2019) of art, nation and heritage. It will combine critical art historical and museological research with participatory ML design, and embed creative activations of interactive ML in the form of artists digital commissions. 

Your profile

You will have a PhD in a relevant area of arts, design, communication or related area with an excellent record of research dissemination (e.g. through exhibition, performance, publication and conference presentation).

You will have the ability to lead the academic and/or professional development of your own area of expertise and to communicate ideas clearly and persuasively, summarising and interpreting complex, conceptual and specialist matters/information accurately. 

You will have experience of designing and building ML systems for real-world use by end users who are not ML experts, for instance in application domains such as the Arts, Digital Humanities, Healthcare, Accessibility, etc. 

You will have experience in building and training ML models for Natural Language Processing and/or Media (sound/image) analysis using Python, and experience integrating user centred design outcomes into the development and evaluation of new technologies.

For further details and to apply please click the apply button.

Closing date: 3rd January 2022 23:55.

UAL is committed to creating diverse and inclusive environments for all staff and students to work and learn – a university where we can be ourselves and reach our full potential. We offer a range of family friendly, inclusive employment policies, flexible working arrangements and Staff Support Networks. We welcome applicants from dverse backgrounds, including race, disability, age, sex, gender identity, sexual orientation, religion and belief, marriage and civil partnership, pregnancy and maternity, and caring responsibility.

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