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Research Assistant (Transforming Collections)

University Of The Arts London

Location: London
Salary: £35,468 to £43,558 pro rata per annum
Hours: Part Time
Contract Type: Fixed-Term/Contract
Placed On: 25th November 2021
Closes: 3rd January 2022
Job Ref: 7532
 

We are seeking a Research Assistant to work in a team creating user interactive machine learning tools for use with archives and collections. Experience in user centred design, interaction design, or other participatory technology approaches is essential. Experience working with technical prototyping environments, including the use of interactive prototyping through computer programming would be an advantage.   

As Research Assistant, you will report to Co-Investigators based at UAL's Creative Computing Institute (CCI), working towards the design and development of Machine Learning systems for end-users through interaction with partners from 15 collections. You will also collaborate with Co-Investigators across other strands of the project to synthesise outcomes. You will support the design and delivery of participatory workshops/seminars with Project Partners, Collaborating Organisations and diverse stakeholders, reporting findings from these workshops so they can be integrated into the design of new tools. You will have responsibility for maintaining and contributing to software projects using Git, and contribute to academic reporting (e.g., conference/symposium papers and journal articles). You will be expected to work effectively and collaboratively with other core team members to ensure that project deliverables are successfully met. 

You will participate in regular project team meetings and a peer support network of the project’s researchers. You will develop your 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 IRO (Independent Research Organisation) partner, and a further 14 Project Partners and Collaborating Organisations across the UK.   

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 machine learning design, and embed creative activations of interactive machine learning in the form of artists digital commissions.  

Your profile

You will have a Masters or 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 work on 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 for diverse and wide-ranging audiences.

You have some experience designing and building computer systems for real-world use by end users and are excited to create new Machine Learning systems for users who are not machine learning experts. You have experience working with computer programming tools to develop prototypes, and knowledge of relevant HCI literature.  

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

Closing date: 3 January 2022 at 23:55.

Interviews will be held on either 17 or 19 January 2022.

Please contact RKEEstaffrecruitment@arts.ac.uk before 22 December 2021 should you have any queries.

UAL welcomes applicants from diverse 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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