Mon 04 Mar
|University of Brighton
Artificial Intelligence (AI) for analysing Covid-related Mass Observation Data – Closed
Time & Location
04 Mar 2024, 00:00 – 12:00
University of Brighton, Lewes Rd, Brighton and Hove, Brighton BN2 4GJ, UK
About the event
Applications are invited for a student/researcher to undertake an internship, supported by a stipend, to develop their skills for facilitating access and analysis of large-scale Covid-related mass observation data. The internship seeks to develop skills in AI-based methods to enhance access and analysis of textual material collected by Mass Observation during the COVID-19 pandemic.
Context
This internship will form part of the collaboration between the project on Digital Skills in Visual and Material Culture, University of Brighton and the Mass Observation Project.
The Mass Observation Project (MOP) is a unique national life-writing project that captures the experiences, thoughts and opinions of “everyday” people in 21st-century Britain. In March 2020, the Mass-Observation Archive launched an appeal for diaries and writing created during the pandemic by people living in the UK. This Covid-19 collection database currently holds thousands of records including directive responses/narratives written by volunteers reflecting their thoughts; diary submissions; annual 12th May day diaries; and biographical information.
The internship will enable the student/researcher to contribute towards the analysis and better understanding of the Covid-19 collection held at the Mass Observation Project database. Besides developing the digital skills of the intern, the internship will support the work necessary to make the database’s records accessible and open for wider research as well as creative purposes.
Internship
During the internship, in consultation with the project team, the student/researcher will:
1) Deploy named-entity recognition and topic modelling techniques to analyse text data in the Covid-related Mass Observation dataset.
2) Produce a series of JupyterNotebooks with code to access and analyse the COVID-related Mass Observation dataset.
The internship requires 4 weeks of work (flexibly arranged) between mid-March and May and will be supported with a stipend of £1,500. The intern will work at the premises of the University of Brighton (Cockcroft Building). The intern will be supervised by Dr Karina Rodriguez Echavarria and Dr. Bayode Ogunleye.
The successful intern will be asked to participate in an optional evaluation reflecting on their placement and skills development to inform research on Digital Skills in Visual and Material Culture.
Requirements
It is expected that the criteria below regarding knowledge, qualifications and interest will be met by the successful candidate. It is essential they have:
Being a student or holding a degree in Computing, Software development or a related discipline.
Good skills in the Python programming language, Markdown and HTML languages.
Demonstrable experience in machine-learning algorithms, including coursework or self-learning projects.
Demonstrable experience in software development projects, including coursework graded with marks above 70.
Experience with Jupyter Notebooks, including using tools such as Anaconda or Google Colab.
Excellent written communication skills
Excellent team working skills
To apply
The deadline for applications is by the end of the 4th of March, 2024. Please send your CV and an expression of interest with evidence of how you meet the requirements for the internship to: k.rodriguez@brighton.ac.uk