Research Assistant

Research Assistant in Business Analytics (up to a maximum of 6.5 hours per week for 24 weeks)

This part-time role (up to a maximum of 6.5 hours per week) will support research carried out in the newly launched QBS Analytics Lab and the wider Department of Information Technology, Analytics and Operations with their research.

We are seeking applicants who wish to gain first-hand experience of conducting research in business analytics, and who have an interest in communicating research to non-academic stakeholders.

This part-time role is intended for an individual who is currently undertaking a Master's degree in Business Analytics in the Business School and who intends to apply to undertake a PhD in the school. Candidates will be required to include a summary of up to one page outlining the intended PhD research as part of the application. However, the application to undertake a PhD is a separate competitive process which is not linked to the application for this post.

Currently undertaking an MSc Business Analytics degree in the business school.

Knowledge of the research process, to include literature reviews and research project design and administration.

Knowledge of appropriate analytics methods.

Excellent written and verbal communication skills are also necessary.

Job Title:  Digital Fingerprinting Feature Engineering 

Nvidia CSIT Cyber-AI hub intern in feature engineering (up to a maximum of 15 hours per week for 20 weeks). 

The successful candidate will be working as an intern with the Nvidia CSIT Cyber-AI Hub project team on preparing data from multiple sources for AI training. This includes proper data storage, organization, cleaning and feature engineering/preprocessing tasks. 

The candidate will help to improve the current feature selection and engineering process for the development of the behavioral model proposed by the team. In addition, and upon obtaining successful results, the candidate is expected to assist with the integration of the software in the Nvidia Morpheus github page. 

Degree in Computer Science or in a relevant field. 

Have, or be about to obtain an artificial intelligence related postgraduate degree. 

Essential criteria: 

In depth knowledge of Artificial Intelligent/Machine Learning concepts 

Experience in data management for AI training. 

Understanding in networking and security best practices. 

Strong programming skills (Python) 

Proficient Linux/Windows skills. 

Desirable criteria: 

Experience with ML projects including feature engineering 

Understanding of cyber security concepts, e.g. Cyber Kill Chain and Defense-in-depth. 

Knowledge in the MITRE ATT&CK framework and other threat modelling tools. 

The Policy Institute is looking for a research assistant to work with Professor Duffy at the Policy Institute on a project analysing longitudinal survey datasets to study the evolution of attitudes and values for generations in the UK and worldwide. The project will involve two main tasks, which are expected to last for a total of 10 days, listed below:

Task 1: Longitudinal data cleaning and data visualisation

We want to update a PowerPoint resource pack consisting of c.100 charts using data from sources including Ipsos, Eurostat, the US General Social Survey, the British Social Attitudes, the European Social Survey and more. The research assistant will work with the Policy Institute team updating existing code (currently available in R/Stata) to extend longitudinal series, produce results breakdowns by cohorts/generations and update the charts sourcing using the most recent data points for these studies. 

Task 2: Investigating the divergence between Gen Z men and women 

We would like to produce a new set of c.40 charts, taken from the larger resource pack from Task 1 that split Gen Z men and women over time, on a smaller selection of questions and data sources, where sample size allows. The research assistant will work with the Policy Institute researchers to identify topics and data sources to carry out this task, and then produce a set of visualisations and statistical models to identify any statistically significant differences between Gen Z gender groups. 

FURTHER INFORMATION 

The post is available on a fixed term basis. The research assistant will be able to organise their working hours and patterns with flexibility, but we are aiming to complete work on both tasks by 28th February 2025. 

 

Essential skills: Enrolled in a Bachelor?s degree in a relevant social science discipline (e.g. politics, economics, social sciences, geography, etc.).

Desirable: Enrolled in a postgraduate (eg. MSc/MA/PhD) degree in a relevant social science discipline (e.g. politics, economics, social sciences, geography, etc.).

Essential skills: Knowledge of quantitative research methods. Experience using statistical software including R, Stata and/or SPSS. Experience using PowerPoint. Excellent written and oral communication skills. Punctual, reliable, committed, proactive. Ability to work independently and as part of a team.

Desirable skills: Experience with the analysis of longitudinal survey data. Experience producing charts using Excel and Powerpoint. Interest in public opinion and public attitudes research. Interest in generations research.