Sustainability Research Assistant

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. 

Working with the Director of HR Operations, Head of Contingent Workforce and Procurement Directorate, this role will be responsible for sourcing, collecting, organising, analysing and interrogating all recruitment related spend category data. Findings will be reconciled to recruitment outcomes so that the spend can be attributed to contingent worker salaries and fees, agency placement fees and advertising related recruitment costs, with the overall aim to reduce spend on non-permanent agency costs. All data and analysis to be the presented and translated into information and insight that meets the needs of various stakeholders across the university and will contribute to a drive to reduce overall costs.  

This is a hybrid position, you will be expected to work in the office 2 days per week. 

None

The job holder will source and gather data from known/standard sources - manipulating routine data so it can be interpreted by others. They may be required to select the most appropriate procedure, technique or approach to conduct analysis and research, deciding how to undertake the work as well as analysing, identifying, and interpreting trends. The job holder will be expected to have excellent understanding of specialist tools to extract the data needed as well as an advanced knowledge of Excel, Power BI, Tableau etc. 

•  Work with HR and Procurement teams to investigate and identify all agency and advertising recruitment spend using a variety of systems and platforms. 
• Work with the Recruitment advisers to ascertain the actual status and outcome of all current vacancies.  
• Collaboratively work with internal and external stakeholders to investigate and review the data required to complete the objective of reducing agency spend within Kings for non-permanent staff. 
• Identify activity data for each vacancy advertisement, including views, impressions, applications, shortlisted candidates, and placements, to ascertain value for money and inform future decisions. 
• Produce visualisations and reports (using tools like Tableau, Power BI, and SQL) and present findings to both technical and non-technical stakeholders in a clear, actionable manner showing usage data and trends to inform future sourcing and hiring decisions.  
• Create data dashboards, graphs and visualisations 
• Work with the recruitment team to incorporate data capture and analysis.  
• Support Manager with data analysis for all activity with all external providers. 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post. 

Essential criteria 

​Experience using PowerBI for data analysis and reporting   

​Strong technical skills in data analysis, optimisation, and dashboard creation.  

​Strong analytical skills, with the ability to interpret and synthesise large data sets.  

​Experience of collaboratively working with internal and external stakeholders. 

​Excellent communication and problem-solving abilities.  

​Problem-solving skills with the ability to troubleshoot data issues and improve reporting processes.  

​Strong attention to detail and commitment to data accuracy. 

​Desirable criteria 

​Experience in the higher education sector or a similar environment.  

​Experience working with other data visualisation tools and methodologies. 

Job Title:  Synthetic ML Training Data Generation 

Nvidia CSIT Cyber-AI hub intern in Synthetic ML Training Data Generation (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 to assist the research on generating synthetic network and system logs data in use for ML training. This role involves assisting the creation of robotic-process automation-based tools that simulate the human/machine to machine interactions in an enterprise network. Using the tools created, generate network and machine data for ML training purposes. 

Another main responsibility is to assist the research on using Large-Language Models to generate data that are comparable to the ones that are generated by the aforementioned tools, and indeed real logs and network data. This will require the research and creation of a data comparison tool. 

Degree in Computer Science, Cyber security or in a relevant field. 

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

Essential criteria: 

Advanced Python programming skills. 

In depth knowledge in Artificial Intelligent/Machine Learning 

Prior knowledge of generative-AI and Large-Language Models 

Experience in data management for AI training. 

Proficient Linux and Windows skills and experience in code management. 

Desirable criteria: 

Advanced understanding in networking and security best practices. 

In depth knowledge on cyber security concepts, e.g. Cyber Kill Chain and Defense-in-depth. 

Experience in network administration. 

Working knowledge of network emulation 

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