Research Associate in Greenhouse Gas Inverse Modelling

Location: University of Bristol
Salary: £35,333 -£39,745 per annum
Contract Type: Open ended, fixed term funding until 31/03/2025
Reference: ACAD106593

The Role

Atmospheric observations of greenhouse gases and ozone depleting substances are playing an increasingly important role in evaluating the success of climate agreements. We are seeking a research associate to develop and use greenhouse gas modelling and data analysis frameworks for national and regional emissions evaluation. This work will contribute to several exciting UK-wide and international projects, including:

  • The NERC Highlight Topic InHALE (Investigating HALocarbon impacts on the global Environment), estimating regional emissions of potent greenhouse gases and ozone depleting substances around the world
  • The Horizon Europe project, PARIS (Process Attribution for Regional emIssions), which aims to better understand European greenhouse gas budgets
  • The newly announced UK Emissions Measurement System, developing the next-generation, operational greenhouse gas emissions evaluation system in the UK
  • The project, a cloud-based community platform for greenhouse gas data analysis

The post-holder will use numerical models that simulate the dispersion of greenhouse gases through the atmosphere. These models can be used, in Bayesian inference frameworks, to estimate surface fluxes from the observations. The derived emissions are used to track progress on climate agreements, improve national inventory reports, help decisionmakers effectively target mitigation measures, and learn about natural emissions changes.

What will you be doing?

The postholder will work with UK, European and other international greenhouse gas monitoring networks, particularly AGAGE and NOAA, to interpret global measurement data using atmospheric models. They will have the opportunity to use and develop atmospheric models of varying complexity, and examine regional emissions trends using high-resolution simulations and data. To combine the data and models, and estimate uncertainties, they will develop and use Bayesian "inverse modelling" techniques.

You will work closely with a team of around 10 researchers in the ACRG studying greenhouse gases and ozone depleting substances, with seven institutions across the UK and Europe through the InHALE, UK Emissions Measurement System and PARIS projects, and with international colleagues in the AGAGE and NOAA networks. Our team are key members of international activities such as the Advanced Global Atmospheric Gases Experiment (AGAGE), with whom you will work closely. You will have the opportunity to participate in the development of the new machine learning approaches and a cloud-based GHG analysis platform, Through InHALE you will work, on a day-to-day basis, with researchers from around the UK (and worldwide) studying the environmental impacts of ODSs and HFCs.

You should apply if

  • You are an ambitious, self-motivated researcher who holds, or expects to obtain, a PhD in physical sciences, computing, mathematics, or similar fields.
  • A high level of computational expertise is essential.
  • Familiarity with Bayesian methods and or atmospheric science is desirable.
  • Excellent communication and teamworking skills are essential.
  • The contract will initially be for a 2-year period and can likely be extended, if mutually agreeable.
  • The post is available to start as soon as possible.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives - particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.


  • Determine the drivers of global trends in ODS and HFC concentrations that we observe in atmospheric data by using, and further developing global atmospheric transport models of varying complexity including Bayesian methods.
  • Use these tools to calculate global atmospheric emissions of halocarbons, and compare the estimates to “bottom-up” (inventory-based) models.
  • Where discrepancies exist, you will examine regional data and models, to determine the causes
  • Participate in the development of new machine learning approaches and a cloud-based GHG analysis platform,
  • Work with a team of 10 researchers and PhD students in the School of Geographical Sciences and Atmospheric Chemistry Research Group (ACRG), developing modelling infrastructure
  • Disseminate findings through peer-reviewed publications and at national and international conferences

For further details about the post you are invited to contact, Professor Matt Rigby

The application deadline is midnight on the closing date. If you need assistance, email Quote reference ACAD106593 on all correspondence./p>

Closing Date: Wednesday 22 February 2023

Interview Date: To be confirmed

published: 25 January 2023     Please mention EARTHWORKS when responding to this advertisement.