NZPS Projects
Applications for 2026 have now closed, applications for 2027 projects will open in October 2026.
Northumbria University Projects
Ref: 2603/NZPS/NU/Rutter
Snow, Light and Life Beneath the Ice: Low-Carbon Approaches to Understanding Winter Carbon Dynamics in Arctic Lakes
Lead Supervisor: Nick Rutter, Northumbria University
We welcome applications from enthusiastic and motivated students with a degree in physical geography, environmental science, Earth sciences, or closely related quantitative disciplines. Prior experience with fieldwork, data analysis, or environmental instrumentation is helpful, but not essential. Full training will be provided.
Ref: 2607/NZPS/NU/Banwell
The Role of Landfast Sea Ice in Antarctic Ice Shelf Stability: Integrating Earth Observation with Low-Carbon AI Modelling
Lead Supervisor: Alison Banwell, Northumbria University
We seek a motivated candidate with strong quantitative and analytical skills, and a degree in Earth sciences, physical geography, environmental science, engineering, applied mathematics, computer science or similar. An interest in glaciology, sea ice, climate science and/or AI is essential. Experience with GIS, Python, Matlab, or numerical data analysis is desirable, and prior exposure to AI modelling would be advantageous but not required. The student should be enthusiastic about interdisciplinary research and collaborative teamwork.
Ref: 2617/NZPS/NU/Pearce
Developing Net Zero Solutions for Autonomous Polar Atmospheric Monitoring of Biological Aerosols
Lead Supervisor: David Pearce, Northumbria University
As a strongly interdisciplinary project, this studentship would be suitable for students with a wide range of backgrounds including a degree in Engineering, Physics or Biology, including those with a background in Microbiology, Ecology, Molecular Ecology, Environmental Physics, Physical Modelling or Atmospheric Science. Students with a background in Ecological Modelling are also particularly encouraged to apply.
Ref: 2619/NZPS/NU/Longman
Reducing the carbon footprint of polar volcano-ice research: Re-using model and cores to understand Antarctic volcanic feedbacks
Lead Supervisor: Jack Longman, Northumbria University
This project would be suitable for students with a degree in geology, physical geography, physics or mathematics. An understanding of volcanology and/or glaciology is advantageous, but not required.
Ref: 2622/NZPS/NU/Prendergast-Miller
Prevalence of textile microfibres in Antarctica: exploring the circularity and carbon footprint of textiles in polar fieldwork
Lead Supervisor: Miranda Prendergast-Miller, Northumbria University
This project would be suitable for a student with a degree in environmental science, forensic science, textile science, life cycle assessments or closely related subjects. We are looking for an enthusiastic candidate, who is willing to develop skills and knowledge outside of their core discipline and has experience in working across disciplines.
Ref: 2623/NZPS/NU/Winter
Low-carbon polar research: Using archived geological samples and satellite data to track Antarctic nutrient flux in a changing climate
Lead Supervisor: Kate Winter, Northumbria University
This project would be suitable for students with a degree in geology, geoscience, physical geography or a related discipline. An understanding of glaciology is advantageous, but not a requirement.
Ref: 2638/NZPS/NU/Sandells
Low-Carbon Snow Microstructure Retrieval from Multi-Frequency Satellite Data Assimilation
Lead Supervisor: Melody Sandells, Northumbria University
This project is suitable for candidates with a numerical background e.g. maths, physics, computational sciences and preferably interest in cold environments, remote sensing and data analysis.
Ref: 2639/NZPS/NU/Markowska
The polar-tropical climate connection: ice sheet controls on subtropical hydroclimate
Lead Supervisor: Monika Markowska, Northumbria University
Suitable for students with backgrounds in Earth Sciences, Environmental Science, Physics, Geography, Mathematics, or related fields. Essential: interest in climate dynamics, basic programming or willingness to learn. Desirable: experience with data analysis (particularly R statistical software package), numerical methods, or track record in climate science research.
Ref: 2648/NZPS/NU/Warren
Drone-borne radar for sustainable monitoring of permafrost thaw and carbon emissions
Lead Supervisor: Craig Warren, Northumbria University
A background in a quantitative subject area, for example geophysics, physics, maths, computing, or other cognate discipline. You would have an interest in the environmental application of your skills, and be passionate about communicating the importance of climate science to stakeholders.
Ref: 2649/NZPS/NU/Alex
Mineral Weathering Controls on Arctic CO₂ Budgets: Quantifying the Hidden Permafrost Carbon Source
Lead Supervisor: Aleena Alex, Northumbria University
This project suits students with a degree in Civil/Environmental Engineering, Geosciences, Chemistry, Material Science, Computational Physics or Chemistry or any related fields. Strong computational and numerical skills—prior programming experience (MATLAB, Python or running MD simulations – LAMMPS) is highly valued. Background in geochemistry, thermodynamics or reaction kinetics is advantageous but not required. The project offers training in kinetic Monte Carlo simulation, geochemical analysis and Arctic field work. Enthusiasm for tackling complex environmental problems using computational approaches is key.
Lancaster University Projects
Ref: 2615/NZPS/LU/Miles
Towards low-carbon satellite monitoring of Greenland’s supraglacial lakes: A year-round, multi-sensor approach
Lead Supervisor: Katie Miles, Lancaster University
This project would be suitable for students with a degree in physical sciences or a closely related subject. Students should be interested in glaciology, remote sensing, and supraglacial lake processes and monitoring. Experience of working with geospatial data, particularly remote sensing methods, is desirable but not essential. Applicants would normally be expected to hold at least a 2:1 UK Honours degree or equivalent, but experience in relevant fields through non-traditional routes is also encouraged. We welcome applications from candidates from all backgrounds.
Ref: 2620/NZPS/LU/Leeson
Thawing Greenland, Powering Tomorrow: Dynamic ice sheet hydrology for Sustainable Energy
Lead Supervisor: Amber Leeson, Lancaster University
The ideal student will have a background in geography, environmental science, earth sciences, or engineering, with an interest in climate, ice-sheet dynamics, and hydrology. Basic experience in Python, GIS, or data analysis is desirable, while previous exposure to hydrological modelling would be advantageous but not essential. The student should be enthusiastic about interdisciplinary research, willing to learn new computational and analytical skills, and able to work collaboratively within a research team, including engagement with partners such as Asiaq Greenland Survey.
Ref: 2642/NZPS/LU/McMillan
Arctic Ice Loss in High Definition – Developing Carbon-Conscious Satellite Workflows for Monitoring 21st Century Glacier Change
Lead Supervisor: Mal McMillan, Lancaster University
Particularly suited to applicants with quantitative skills and background in mathematics, computer science, physics, data science, engineering, environmental science or geography who want to use numeric techniques to study environmental science and climate change.
Ref: 2646/NZPS/LU/Hossaini
The Role of Sea Ice and Snow in Shaping Atmospheric Chemistry in a Changing Climate: Reducing Uncertainty with Computationally Efficient Gaussian Process Emulation
Lead Supervisor: Ryan Hossaini , Lancaster University
Well suited to students with academic background in physics, chemistry, environmental/earth sciences, or another suitably quantitative discipline. Aptitude for scientific computing and programming advantageous. Strong interest in climate, atmospheric and/or polar science particularly valuable. Enthusiastic about interdisciplinary research.
University of Leeds Projects
Ref: 2612/NZPS/UoL/Watson
Citizen Science and Remote Sensing for Net Zero-aligned Glacial Lake Monitoring
Lead Supervisor: C. Scott Watson, University of Leeds
This project would be suitable for students with a good first degree (1 or high 2i) in geography/ GIS/ earth sciences/ glaciology/ or related discipline. A masters degree would be advantageous and experience in computer programming (e.g., R, Python, MATLAB) and fieldwork skills are desirable but not essential, since training will be provided.
Ref: 2616/NZPS/UoL/Elliott
Low-Carbon Earth Observation of Arctic Permafrost Thaw and Tundra Fires: Reducing the Carbon Footprint of Big Data Processing
Lead Supervisor: John Elliott, University of Leeds
This project would be suitable for students with a degree in physical sciences (or a closely related subject). The candidate would need some experience with programming and data analysis as well as an interest in working with large satellite datasets applied to environmental problems in the Arctic.
Ref: 2626/NZPS/UoL/Ilyinskaya
Low-carbon wildfire forecasting for Arctic ecosystems using satellite remote sensing
Lead Supervisor: Evgenia Ilyinskaya, University of Leeds
We seek a student with an enthusiasm for interdisciplinary research—combining remote sensing, laboratory work, and hazard analysis. Experience with handling large datasets, such as coding for data analysis (e.g., Python, R, or similar) is desirable but not mandatory. A background in geophysics, geology, physics, environmental science, or a related quantitative discipline is ideal. Prior experience with satellite imagery, or machine learning would be advantageous.
Ref: 2627/NZPS/UoL/Piazolo
How does viscous anisotropy affect ice sheet dynamics and in turn sea-level rise? Gaining insights using low carbon footprint techniques such as modelling and remote sensing
Lead Supervisor: Sandra Piazolo, University of Leeds
This project would be suitable for students with a degree in mathematics, physics, geoscience or a closely related subject. Students are expected to have a high level of numeracy, ability to code, and interest in working in an interdisciplinary environment developing green skills.
Ref: 2630/NZPS/UoL/SurawyStepney
Resource efficient simulation of the West Antarctic Ice Sheet with machine learning
Lead Supervisor: Trystan Surawy-Stepney, University of Leeds
Suitable for ambitious, mathematically-minded students with very good undergraduate or Masters degree in physics, mathematics, computer science, engineering or related discipline. Understanding of programming (Python, Julia, C) highly valued but not required. Interest in and aptitude for mathematics essential.
Ref: 2631/NZPS/UoL/Neely
Sustainably Monitoring the Mass Balance of the Greenland Ice Sheet
Lead Supervisor: Ryan Neely, University of Leeds
Suitable for students with degree in atmospheric science, environmental science, physics, engineering, mathematics, or closely related discipline. Strong quantitative and analytical skills with experience in data analysis, numerical modelling, or instrument development. Programming skills (Python) and interest in renewable energy systems highly desirable.
Ref: 2633/NZPS/UoL/Craig
Low-carbon monitoring of Southern Ocean temperature variations using earthquake-generated seismic waves
Lead Supervisor: Tim Craig, University of Leeds
This project would suit a physicist, geophysicist, oceanographer, quantitative Earth scientist or geologist, or mathematician. Candidates will need a strong background in numerical data handling and analysis. Prior skills with coding would be an asset, as would prior experience with either seismic or acoustic data, or physical oceanography, although training in all of these will be provided during the studentship.
Ref: 2635/NZPS/UoL/Whale
Sustainable In-situ Atmospheric Sensing: Advancing Balloon-borne Observations of Polar Cirrus Clouds
Lead Supervisor: Thomas Whale, University of Leeds
Well suited to students with academic background in physics, chemistry, environmental/earth sciences, or another suitably quantitative discipline. Aptitude for scientific computing and programming advantageous. Strong interest in climate, atmospheric and/or polar science particularly valuable. Enthusiastic about interdisciplinary research.
Ref: 2645/NZPS/UoL/Murray
Autonomous Ice-Nucleating Particle Monitoring with Minimal Carbon Footprint
Lead Supervisor: Benjamin J. Murray, University of Leeds
An undergraduate or postgraduate qualification in an appropriate physical science.
University of Reading Projects
Ref: 2613/NZPS/UoR/Feltham
Using machine learning to cut the carbon cost of sea ice simulation
Lead Supervisor: Danny Feltham, University of Reading
The successful candidate will have a degree in physics, applied mathematics, computer science, engineering, or a similar numerate subject such as meteorology, along with an aptitude and enthusiasm for solving real world problems and computer programming. The candidate should be able to work independently and in groups and be enthusiastic. While knowledge of the climate system, oceanography, sea ice, or meteorology would be ideal, this knowledge can be taught to the right candidate.
Ref: 2651/NZPS/UoR/Robson
Arctic Dense Water Formation and AMOC Resilience: Balancing Climate Model resolution with Carbon Footprint
Lead Supervisor: Jon Robson, NCAS, University of Reading
We are looking for an enthusiastic student with a science background from subjects like physics, mathematics, meteorology, environmental/earth science. The student is expected to have interest in programming and data analysis required for the analysis of big climate data sets.
British Antarctic Survey Projects
Ref: 2602/NZPS/BAS/Orr
Cutting the Carbon Cost of Climate Models: Using AI to Predict Greenland Precipitation and Ice Sheet Change
Lead Supervisor: Andrew Orr, British Antarctic Survey
This project would be suitable for students with a degree in meteorology, physics, mathematics or a similar quantitative science. An interest in data analysis and numerical modelling is essential.
Figure caption: Map showing total accumulated snowfall (mm water equivalent) over the GrIS on 14 March 2022 from ERA5 atmospheric reanalysis (from Bailey and Hubbard, 2025). This extreme event was fuelled by an intense atmospheric river (AR) that occurred in March 2022 that delivered 11.6 gigatons of snow over south-east Greenland, offsetting 8% of mass loss and delaying summer melt by 11 days. Typically, the precipitation rates are high over this region of the GrIS, but poorly modelled, which has knock-on impacts for modelling the dynamics of major ice streams in this area.
Ref: 2624/NZPS/BAS/Dornan
Studying Antarctic krill with autonomous platforms to reduce research emissions
Lead Supervisor: Tracey Dornan, British Antarctic Survey
This project would be suitable for students with a degree in Environmental or Marine Science, Marine Ecology, Oceanography, or Data Science including Environmental Statistics. The field of active acoustics requires an aptitude for numeracy, data processing and analysis so candidates must be comfortable with their ability to develop these skills.
Ref: 2628/NZPS/BAS/Heuvel
Optimising Southern Ocean cloud measurements through AI-driven sensor placement for reduced carbon emissions
Lead Supervisor: Floortje Van Den Heuvel, British Antarctic Survey
The project would be suited for a student with a degree in mathematics, physics, atmospheric sciences, computer sciences or a closely related subject. Experience in training deep learning methods is desirable.
Ref: 2629/NZPS/BAS/Bennison
Developing low-carbon approaches to wildlife monitoring in Antarctica
Lead Supervisor: Ashley Bennison, British Antarctic Survey
This project would be suitable for a numerate student with a strong degree in Ecology, Zoology, or closely related subject. A background knowledge of biodiversity conservation is desirable. Experience of working with large multi-faceted datasets including geospatial data would be an advantage, along with experience in the use of Geographic Information Systems (GIS), operation of UAVs and automated sensors. Where these skills are limited, training will be provided.
Ref: 2632/NZPS/BAS/Marsh
Antarctic ice-shelf calving: low-carbon approaches to monitoring edge wasting
Lead Supervisor: Oliver Marsh, British Antarctic Survey
This project would be suitable for students with a degree in Physical Geography, Geophysics, Environmental Science or a closely related subject. Strong mathematical or numerical skills are desirable.
Ref: 2643/NZPS/BAS/Yang
Integrating Low-Carbon Machine Learning With Physical Models to Advance Polar Blowing-Snow Climate Predictions
Lead Supervisor: Xin Yang, British Antarctic Survey
Suitable for students with a degree (2:1 or above) in Physics, Chemistry, Applied Mathematics, Meteorology, Environmental Science, Computer/Data Science, or a related field. Comfortable with programming (Python, Fortran) and keen to engage in modelling, data analysis, and sustainable research workflows. Strong interest in polar science and low-carbon technology is advantageous.