06 Postdoc Positions at Leeds, West Yorkshire, England

Are you an ambitious researcher looking for your next challenge? Do you have interests or background in environmental politics, political ecology or related areas? Do you want to further your career in one of the UKs leading research intensive Universities?

 The Global Methane Politics project (METH-POL) is a five-year European Research Council-funded project led by Professor Jan Selby in the School of Politics and International Studies at Leeds. The overall objectives of this project are to contribute to global climate change research and practice by exploring 1) the distinctive political dynamics and challenges associated with methane emissions and methane emission reduction efforts; and 2) why methane emissions are proving so hard to control, despite their acknowledged importance as a short-term climate forcer and the abundance of low-cost technical mitigation solutions. The project will involve research across five major methane emitting sectors – livestock, oil and gas, solid waste, coal, and wastewater – and in more than a dozen countries spanning global North and South, and every continent. The project adopts a broadly political ecology theoretical approach, and will involve research at many different scales, from international policy arenas right down to the level of individual mines, farms and treatment plants where methane is emitted and governed in practice. The project will principally make use of qualitative methods, especially documentary analysis, interviews and observations.

 The 3 Research Fellows will join the project for three years from September 2026, focusing respectively on 1) livestock, 2) oil and gas, and 3) solid waste. For each of these fellowships, the core objectives will be to generate original research findings on their specific sector; to work with other members of the project team (the PI, project administrator, two PhD researchers, and other research fellows) to compare across sites, scales and sectors; and to explore the broader implications of these sectoral and comparative findings for methane and climate research and practice.

The project will develop state of the art climate tools to accurately predict the dispersal and climate impact of proposed hypothetical stratospheric aerosol injection strategies. You will be working as part of an international interdisciplinary team to reduce some of the fundamental climate modelling uncertainties around solar radiation modification (SRM). This is a 24-month fixed term contract. 

This role will entail simulating the distribution of radiatively active aerosol tracers injected into the stratosphere within the Whole Atmosphere Community Climate Model (WACCM). Working with Prof Dan Marsh, you will setup, run and analyse a variety of simulations to simulate the radiative and climate effects of aerosol injection. You will be part of a project team to design, implement and analyse data from a series of sensitivity experiments. With Prof. Piers Forster, you will estimate the effective radiative forcing from injecting stratospheric aerosols. Liaising with a wider international team, you will contribute to project report writing and dissemination of scientific results at conferences and in peer-reviewed literature.

It is clear that SRM is a controversial subject, and our desire is to be as transparent as possible, as no such confidentiality agreements will need to be signed, and all the work conducted under this project will be communicated openly, entering the public domain through peer reviewed publications.

You will have a PhD (or have submitted your thesis before taking up the role) in the field of Physics or Atmospheric, Ocean or Climate Science, or Computing and have extensive experience of using and analysing data from climate models. Prior experience with the WACCM or similar model will be a strong advantage. Experience communicating your science to policy makers is desirable.

We are looking for a Research Fellow in Techno-Economic Modelling for Sustainable Protein Production to join our international and interdisciplinary team developing an open-source AI platform for microbial protein from agri-food waste-streams, which has recently been awarded £2M from the Bezos Earth Fund as part of their AI for Nature and Climate Grand Challenge.

Nearly 29% of the world’s population faces food insecurity, yet millions of tonnes of nutrient-rich agri-food waste is generated globally each day. This waste can be upcycled into sustainable, high-quality microbial protein (e.g. yeast, fungi, bacteria and algae) via fermentation for use as ingredients in existing foods or to produce novel meat and dairy alternatives. However, microbial fermentation processes are difficult to design, optimise and scale up, especially for complex, and highly variable waste streams. This limits their investment attractiveness and economic viability, especially for small and medium enterprises (SMEs), and ultimately their global adoption.  

The University of Leeds in collaboration with the Commonwealth Science and Innovation Research Organisation (Commonwealth Scientific and Industrial Research Organisation, Australian Government – CSIRO) in Australia will develop the world’s first open-access AI platform to address these challenges by streamlining the development of microbial protein production processes. Leveraging advances in modern AI, the platform will consist of a Waste to Protein AI Engine coupled with an adaptive user interface enabling users to input their waste composition, volume, and location and immediately receive actionable insights, such as optimised fermentation parameters, microbial strain recommendations, projected protein yields and economic returns. Our AI platform will also provide users with an R&D roadmap that recommends critical trials to perform during process development and scale-up to reduce experimentation needs and provide partnership recommendations for areas where they lack expertise, facilities or market access. 

You will be based in the Food AI Lab (www.foodailab.co.uk) in the School of Food Science and Nutrition and benefit from engaging with the growing AI, Alternative Protein and Food activities at the University of Leeds including the National Alternative Protein Innovation Centre (National Alternative Protein Innovation Centre (NAPIC) – NAPIC) the Leeds Institute for Data Analytics Food Community (LIDA: Food | Leeds Institute for Data Analytics) and the Global Food and Environmental Institute (Global Food and Environment Institute | University of Leeds). You will also benefit from collaborating with CSIRO and numerous industry partners in the UK and across the globe.

You will have a PhD (or near to completion) in Engineering, Food Science, Computer Science or a closely allied discipline; a background in techno-economic modelling and research experience in food or bioprocess design. You will have a proven ability to work well both individually and, in a team, including partners from other countries, disciplines and industry.

You will become a key member of the Ice Nucleation group in the School of Earth and Environment at the University of Leeds. You will work on the M-Phase (Resolving climate sensitivity associated with shallow mixed phase cloud in the oceanic mid- to high latitudes) and also the new IceSO (Measuring the variability in ice-nucleating particles over the Southern Ocean to reduce uncertainty in cloud-climate feedbacks) projects.  These projects are tackling important questions at the core of one of the largest uncertainties in global climate projections – the properties of low-level oceanic clouds and the influence or aerosol particles. Model radiative biases over the Southern Ocean (SO) are largely due to a lack of low-level supercooled liquid clouds that results in far too much solar radiation making it to the surface, a sea that is too warm and global cloud feedback that is too negative. The balance between supercooled water and ice is central to defining the effects of clouds on climate and climate change, yet this balance is very poorly represented by current climate models. A key goal is to substantially improve our understanding of the sources and properties of the ice-nucleating particles (INPs) that initiate these critical changes in cloud phase, and thereby reduce uncertainty in climate projections.

Our knowledge of the enigmatic particles that trigger ice formation in clouds is particularly poor for remote oceans, such as the SO. Available data are limited by being of low time resolution (many hours to days) and short-term campaign-based (weeks, months) that only provide a snapshot. The available measurements show substantial variability in INP concentrations, and an unexplained decrease in SO INP concentrations over several decades. 

At present we do not understand short- or long-term variability in INP and furthermore the sources, seasonal cycle and temperature dependence of INPs remain poorly defined; this hinders the development of realistic treatments of cloud physics in climate models. To accurately represent INPs in our models we need long-term high time resolution (~1 hr or better) measurements, but until now we have not had the tools to make these measurements. We have broken this deadlock with the development of PINE (Portable Ice Nucleation Experiment), a mobile cloud chamber, which we propose to deploy in the SO region. In IceSO PINE will be installed at the Kennaook/Cape Grim Baseline Air Pollution Station (KCG-BAPS; 40°S, 144°E) through our partners at CSIRO (Ruhi Humphries). KCG-BAPS is situated at the latitude band of greatest low-cloud feedback on Earth and has been used as a SO baseline station for over 40 years. 

You will work closely with Dr Mark Tarn (Leeds), who led the M-Phase cruise and collected filter samples from the FAAM aircraft that we will study with electron microscopy; Dr Ross Herbert (Leeds) and Prof. Ken Carslaw (Leeds), who are our global aerosol modellers who will make use of our new SO data; Dr Paul Field (Leeds and Met Office) who will work with Herbert on cloud modelling; Dr Ruhi Humphries who will assist us in deploying PINE at KCG-BAPS; and Dr Ottmar Möhler who co-developed PINE with Leeds. 

We are looking for a Research Fellow to complete an important role in a UKRI Future Leaders Fellowship project: Glacial Lake Observatory for Flood Hazards Impacted by Changing Climate (GLO-FHICC) led by Dr C. Scott Watson. As glaciers disappear, thousands of glacial lakes are forming. Yet their location in high-altitude and logistically challenging environments means observations are sparse, including essential measurements of water storage and potential flood hazards. This project aims to advance our understanding of glacial lake formation and glacier-related flood hazards, with the goal of improving disaster preparedness and refining projections of glacier evolution across High-Mountain Asia. You will contribute to creating systematic and open access glacial lake monitoring through our Glacial Lake Observatory (http://glacial-lake-observatory.org/). 

In this role, you will develop innovative methods to quantify the morphology and evolutionary trajectories of glacial lakes across High Mountain Asia, by integrating multibeam sonar data, topographic information, and environmental variables with deep learning techniques. You will also contribute to refining digital elevation models (DEMs) and advancing flood hazard modelling in the complex topography of Himalayan catchments. You will work closely with Dr C. Scott Watson and Dr Lauren Rawlins, alongside other project staff, students, and researchers in the Faculty. The position offers exciting opportunities to present your work at national and international conferences, and you will be supported in your professional development through funded training opportunities tailored to your career goals.

You will have, or be close to obtaining, a PhD in deep learning, computational geosciences, computer sciences, mathematics, or physics, and have experience of developing and applying deep learning models.