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Research Assistant (Machine Learning)

Details


1113775


University of Nottingham


01/07/2026


3 Months


5-20 per week to be agreed with the worker (35 hours in total)


Smart Casual

Pay


-


-

Description

Role

We are seeking a Research Assistant in machine learning for a 35-hour short-term contract on a BA/Leverhulme-funded project, "Poverty Amidst Abundance – Tackling Energy Poverty in the UK." The candidate will develop a machine learning pipeline to identify hidden energy vulnerability using the UK's Smart Energy Research Lab(SERL) dataset.

  

Start Date: 01/07/26

End Date: 30/09/26 

Working Hours:  5-20 per week to be agreed with the worker (35 hours in total)

Pay Rate: £18.36 per hour 

Holiday Pay Rate: £2.22 per hour 

Location: Remote working 

Dress code: Smart casual  

Duties and responsibilities

  • Complete the ONS/UKDS "Safe Researcher Training" (SRT) for SecureLab access. 
  • Clean, preprocess, and link large-scale longitudinal datasets. 
  • Develop algorithms for behaviour-based indicators of energy vulnerability. 
  • Build and evaluate a supervised machine learning pipeline focused on imbalanced datasets. 
  • Extract insights using model interpretation techniques. 
  • Produce clean and reproducible Python code while ensuring data privacy.

Skills and experience

Essential: 

  • Pursuing or recently completed a PhD in Mathematics, Data Science, Computer Science, or Statistics. 
  • Proficient in Python and data science libraries (e.g., Pandas, NumPy, Scikit-learn). 
  • Experience with high-dimensional time series data and supervised and unsupervised machine learning. 
  • Familiarity with explainable AI (XAI) techniques, especially SHAP.

Desirable: 

  • Experience with behavioural data. 
  • Understanding of data privacy principles (e.g., GDPR). 
  • Experience in a secure data environment is a plus, but training will be provided.

Location
Remote working

How to apply
Please apply here! 

Ensure that you demonstrate how you meet the requirements outlined above in your written application. You will always need to tailor your application to the role you are applying for. 

Applications may close early if a suitable candidate is found, so apply early to avoid disappointment. 

 

The Flexible Staffing Team at the University of Nottingham are committed to promoting equality of opportunity, and we welcome applications from candidates who reflect the diversity of our communities. 

 

If you require any reasonable adjustments to be made during the recruitment process on account of a disability or other health-related condition, please contact the team at FlexibleStaffing@nottingham.ac.uk 

 

To hear about our other roles, please register online at https://portal.unitemps.com/register/candidate and sign up to emailed job alerts. 

 

This is a Unitemps role at the University of Nottingham which has been advertised by the Flexible Staffing Team. By applying for this role, you are agreeing to that we will share your application information with the recruiter for this role within UoN. Your details will be processed in accordance with our Privacy Notice which can be found on our website. If your application is successful, you will need to complete an eligibility to work check prior to commencing work.