Research Assistant New

Job Description

To support a project on evaluating whether real-time student feedback improves assessment design, making the process more fair, inclusive and transparent. The research involves analysing focus groups notes, student feedback and grade performance surveys. 

The role includes conducting thematic analyses and working with quantitative data. The successful candidate will be supported in developing their qualitative and quantitative research skills through guidance towards self-directed learning resources and ad-hoc training to enhance their expertise. 

The Research Assistant will contribute to generating meaningful insights to inform educational practices, particularly in assessment co-creation and design.

Key responsibilities:

1. Clean, process and manage datasets from multiple sources for analysis.
2. Provide quantitative and qualitative research support.
3. Assist in conducting thematic analyses to identify themes from qualitative data.
4. Perform quantitative analysis of student grade performance.
5. Participate in discussions, communicating and presenting research at meetings.
6. Contribute to writing reports, presentations and academic publications.

We welcome applicants from diverse backgrounds and are committed to creating and inclusive research environment.

A first degree in a relevant subject area (or have equivalent experience) or currently enrolled in their final year of an undergraduate degree in a relevant subject area (or have equivalent experience).

Desirable: Currently enrolled in a PhD programme in a relevant subject area.

1. Knowledge of qualitative and quantitative research methods and techniques.
2. Some understanding of thematic analysis and experience in working with large datasets. 
3. Some relevant experience with qualitative data analysis software (e.g. NVivo) and econometric software (e.g. Stata, R or Python).
4. Ability to work independently and collaboratively remotely.
5. Ability to manage tasks and deliver results under tight deadlines.
6. Strong work ethic, commitment to data accuracy.
7. Ability to work with limited supervision.