Summer Internships in Sustiability Experimental and Data analytics research for Undergraduate UK-based students

Heriot-Watt application call for Vacational summer internship for undegraduate students (not fresh graduates). GeoDataScience group offers a number of summer internship topics related on sustainability experimental and data analutics research:

Proposal 7 (SoSS): Co‑Designing Sustainability Surveys with AI: Investigating Policy, Equity, and Environmental Considerations​
Supervisors: Dr Kate Schmidt Sullivan (SoSS); co-supervisor Dr Farah Rabie (EGIS)
Email: k.sullivan@hw.ac.uk , F.Rabie@hw.ac.uk

Project overview:

This interdisciplinary project will support a student to investigate the use of AI agents to augment sustainability-focused survey design. The project aims to examine whether and to what extent responsible AI-supported survey development can inform institutional sustainability decision-making, encompassing a key principle of the university’s Climate Action Framework and an EPSRC research theme. Working with researchers from EGIS and SoSS, with input from the university’s Global Environmental Sustainability team, the student will iteratively develop and evaluate AI-assisted surveys in three contexts: policy-informed prompts for measuring initiative impact; equity-focused prompts for engaging underrepresented groups; and AI-accelerated workflows accounting for environmental footprint.

The project is also supported by HWU Sustainability team.

Proposal 4 (EGIS): Experimental Evaluation of Heriot-Watt campus Flood sustainability with Rainfall Simulator 
Supervisor: Prof V. Demyanov (co-supervisors Ms Elise Cheng and Dr Anna Clark)
Email: v.demyanov@hw.ac.uk 

Project overview: Sustainable Urban Drainage Systems (SuDS) provide flood mitigation and biodiversity benefits. Rain gardens SuDS, lack standardised guidance on soils, vegetation, and drainage design. This has created uncertainty around their true soil attenuation capacity and performance. The internship will experimentally compare on-campus vegetated plots and real, functioning SuDS under controlled rainfall simulation conditions using an original rainfall simulator developed at HWU. Testing of multiple sites will reveal how campus locations respond to intense rainfall events. The project will deliver a quantitative assessment of HWU’s natural drainage and strengthen Nature based Solutions research. 

Internship conditions:

We are looking for keen candidates among UG2-3 year or pre-finalyear MSc/MEng students.

The 10-week EPSRC Vacation Internship Programme, funded by the Engineering and Physical Sciences Research Council (EPSRC), gives undergraduate students the opportunity to be part of a unique research experience.

 As an intern, you will spend 10 weeks working on various elements of research, such as literature reviews, project planning, analysis, and reporting to get a feel for what it is like to be a researcher. 

 Interns will be paid the Real Living Wage of £13.45 per hour and will have access to £200 for consumables. Undergraduate students both internal and external to our university can apply, so long as the eligibility criteria outlined below is met.

Eligibility criteria

Eligible applicants should:

• Be studying within the field of the proposed project (see below link to available projects)
• Be able to fulfil a 10-week internship (35 hours a week) at our Edinburgh campus, beginning in June 2026.
• Be studying on a middle year of their degree. Students should not be in their final-year and should not be in their first-year of their degree.
• Have excellent verbal and written communication skills
• Have good attention to detail
• Should be living in the UK at the moment of applying

How to apply

The application form, role description and list of available vacation internship projects can all be found on this form. 

Apply before the deadline on 12 midday on Tuesday 21 April. 

PhD project in AI data analytics for future water security

Edinburgh Research Partnership in Engineering (ERPE) Joint PhD Studentship between Heriot-Watt University and University of Edinburgh.

Starting: September 2025

Application deadline: 18th February 2025

We are looking for a motivated and curious PhD candidate to work across Heriot-Watt University and the University of Edinburgh, UK.

Motivation

Climate change is influencing UK water resources, changing temporal and spatial patterns of water availability differentially across the country. Water resources is a data rich field, with long term datasets of meteorological and hydrological data available at different resolutions across the country. Recent research has explored the long-term influence of climate change on British rivers (Wray et al., 2024). The identified trends lead to exposure of regional response patterns. AI pattern recognition applied to spatial-temporal river runoff datasets will help to identify regional trends and the associated impact from climate change. Once trained, these algorithms can be deployed on future climate change projections (e.g. UKCP18 ensembles) to investigate how such patterns (e.g. rapid transitions between wet and dry) evolve in the future.

Aims and objectives

The overarching aim of this thesis is to explore future water resource patterns by examining current trends in hydrological extremes, and identifying regional occurrence of patterns; and using these understand future changes.

This PhD project will focus on application of modern AI algorithms to explore spatial-temporal data from UK rivers. It will entail profiling regional and temporal river runoff to explore spatio-temporal trends and identify extreme event occurrences. Feature selection will enable exploration of the driving stressors of hydrological events.

This is an exciting opportunity for the right candidate to tackle the challenge of climate change in water resources for future water security by analysing big data (national scale long-term hydrological data) using cutting edge data mining and AI tech to develop bespoke understanding and solutions.

Requirements

Engineering/physics/data science degree; ability to handle large datasets, coding skills in an advanced language (e.g., Python, or R).

Research environment and supervision

The successful candidate will be co-supervised by Prof Lindsay Beevers at the University of Edinburgh, Associate Professor Sandhya Patidar and Prof Vasily Demyanov at Heriot-Watt University as part of the Edinburgh Research Partnership in Engineering (ERPE). ERPE is a strategic alliance between Heriot-Watt University and the University of Edinburgh as two of the UK’s leading research universities in STEM. ERPE works with academics, industry and public sector partners to deliver world-leading engineering solutions and create commercial, social, environmental and economic impact.

How to apply
Contact us at l.beevers@ed.ac.uk, s.patidar@hw.ac.uk and V.Demyanov@hw.ac.uk by 18 Feb 2025. Please send your CV, transcripts and a motivation letter. The selected candidate will be invited to apply for the PhD position via the University of Edinburgh website by 16:00 on Friday, 28 February (UK time) and will be put forward to a competitive selection process by ERPE.

Comparison of the CC attribution percentage through time across eight first stage metrics for the four Tweed sub-catchments with longest records (from Wray et al., 2024).

Uncertainty quantification of geomechanically sensitive reservoirs using physics infused machine learning – CLOSED

A PhD opening in Uncertainty quantification of geomechanically sensitive reservoirs using physics infused machine learning. The position is fully funded from an industry research project (home tuition fee and stipend) for eligible UK candidates. International candidates will need to self-fund the additional tuition fee of around £20,000 per annum. 
– CLOSED