This session will give participants an insight into who, what, why, where, when and even how journalists and producers gather interviews with academics.

This workshop will give you the confidence and agency to move forward with your career planning, helping you identify personal skills and strengths, success drivers and values, and what this means for your future post PhD.

Participants will understand the methodological underpinnings of sampling in quantitative social sciences research. They will learn to select appropriate sampling procedures, evaluate and critique sampling plans.

This session will reflect on the use of comparative case studies as a research design. It is aimed at students who are undertaking - or plan to undertake - a comparative case research design. It is not primarily aimed at disciplines that have well-developed methodological positions on this approach (e.g. comparative political economy) although researchers from those disciplines are welcome to join us.

The workshop consists of a lecture/seminar and practical research activities where attendees will learn about anthropological approaches to questions of time, history, and their material culture, including archival documents, images, monuments, and commemorative art. Through a series of comparative empirical examples, the workshop will discuss experiences of time as knots rather than lines and explore challenges of interpreting history on the basis of partial records and silenced stories such as stories of slavery and political dissent.

Multilevel modelling is an umbrella term for a wide range of statistical models appropriate for clustered data. Multilevel modelling can be thought of as an extension of the classical Multiple Regression Models that allows the researcher to assess the variation in an outcome of interest at different levels of a predefined hierarchy structure and simultaneously analyse the characteristics associated with that variation.

This workshop aims to introduce and explain what can be described as new materialist approaches to research. It aims to offer first an introduction to new materialist ontology and second an explanation of how this might be translated into a research methodology in the social sciences.

It has long been recognised that diary methods are excellent for capturing people’s daily lived experiences (Bartlett and Milligan, 2020). Diary methods are particularly good at bypassing researcher/researched power relations as the power to document and what to document lies with the participant and not with the researcher.

The UKRI, which governs the advanced research academic sector in the UK, and is home to the Economic and Social Research Council have increasingly demanded stronger awareness of and practice around research integrity. In turn, research integrity is being 'understood' somewhat differently across the disciplines with some dominance of its translation into quantitative research.

This session will draw form a range of qualitative projects  conducted in the UK based and with partners in the Global South to explore and discuss principles of equal partnerships, and meaningful community engagement.

This workshop will take participants through a range of different comparison methods in social science, ranging from the use of analogy and metaphor, through to more systematic methods such as Qualitative Comparative Analysis (QCA).

This workshop will introduce examples of ethnodrama, composite participants and ethical fictionalisation to discuss broader issues of representation of diverse participants’ stories when working with qualitative data.

In this workshop we will discuss what we mean by 'industry partners' and which partners may be relevant for participants' different research areas. We will discuss the value of engaging with industry partners, approaches to building partnerships and what success looks like with good partnership.

This training course provides doctoral students with the necessary methodological tools for policy evaluation. While policy-makers are interested in the causal effects of policy interventions, a perennial problem that makes such assessments difficult is endogeneity, for instance due to reverse causality.

This is an informative, fun and interactive session that introduces you to creative methods and offers guidance on why, when and how you might use them in your research. It starts with an introduction to creative methods and how they relate to epistemological and ontological positions.

Want to become more involved with the private and third sectors? Keen to get your research disseminated in policy and media? Interested in producing impact outwith the academy?

In this workshop we will look at how to make the best use of NVivo in your qualitative data analysis. We will consider which NVivo tools will be most useful for your PhD study and you will see how to set up an NVivo project. We will also cover how to code your data and where to find help when using NVivo. 

We will provide a beginner's introduction to quantitative data visualisation using the statistical programming language R. We expect no prior knowledge of using R, this is meant for complete beginners, but more experienced users are welcome. Our workshop will be structured around a recent tutorial article from our department which provides an online resource for learning data visualisation using R.

This session will explore some key methodological and ethical considerations around working with vulnerable groups.  The session will begin by unpacking and exploring the concept of vulnerability before going discuss methodological and ethical considerations drawing on examples from a range of research studies. 

Drawing on experiences from recent and current research projects this talk shall explore what a Shared Dialogue Workshop is, and why using them can be incredibly powerful in applied research projects.

Machine Learning has become a popular topic in the recent years. e.g., for designing recommendation systems used in YouTube or for building computer vision models used in self-driving cars. In this workshop you will learn some fundamental concepts of machine learning, e.g., model training and validation, hyper parameters tuning etc., and explore some of the mostly commonly used algorithms for both supervised and unsupervised learning, for example, random forest and k-means algorithm.

This session will introduce students to the ideology at the heart of feminist methodologies. Feminist methodologies take particular care to make research inclusive, to foreground the voices of experts and dismantle power imbalances between the researcher and the researched. These approaches come with a particular political understanding of the academy and the research process which we will negotiate.