Post-Doctoral Research Associate: Modelling Atmospheric Oxidation in the Tropics

Cambridge; Lancaster; On-site; GBP 30,000 - 40,000; Full time

Job summary

A prestigious research institution in England is seeking a Post-Doctoral Research Associate for a project focused on atmospheric oxidation in the tropics. This role involves utilizing the UKESM model, analyzing results, and employing machine learning techniques. Candidates should possess a PhD in physical or computational science and ideally have experience in atmospheric modelling. The position offers a collaborative environment with international scientists, starting in March 2026. Applications are now open.

Qualifications

• Must have or be about to obtain a PhD in a relevant field.
• Experience simulating climate or chemistry is desirable.
• Proficiency in Fortran and high performance computing experience is desirable.

Responsibilities

• Perform experiments using the NERC-Met Office UKESM model.
• Analyze model results and assist in emulating results using machine learning.
• Collaborate with scientists globally and with UK Met Office.

Skills

Interpreting large model datasets

Experience with Python

Experience with R

Experience with Matlab

Education

PhD in physical or computational science

Tools

Unified Model

UKESM

Job description

• Post-Doctoral Research Associate: Modelling Atmospheric Oxidation in the Tropics

Post-Doctoral Research Associate: Modelling Atmospheric Oxidation in the Tropics

Limited funding: The funds for this post are available for 42 months in the first instance.

Applications are invited for a PDRA funded through the NERC to join the "Determination of Tropical Oxidising Capacity through model calibration" (DeTOX) project.

The DeTOX project aims to advance our understanding of atmospheric oxidation in the tropics to improve projections of future atmospheric composition in response to climate change and tropical development. The project will provide the first rigorous constraints on oxidation by bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It aims for the first clear attribution of how uncertainty in different physical, chemical and meteorological processes influences our understanding of atmospheric oxidation, and fresh insight into how oxidation may change in future. The project is led by the University of Lancaster and draws on expertise in atmospheric modelling and data science involving partners at six UK institutions and collaborators in the US. You will be embedded in the NCAS@Cambridge group based in the Department of Chemistry at the University of Cambridge.

This post will involve work using the NERC-Met Office UKESM model. Specifically you will perform experiments with the model (including designing the experiments), analysing the results and assist in work to emulate the results using Machine Learning.

The successful applicant will work closely with other scientists in the project based around the world and with the UK Met Office.

Applicants must have (or be about to obtain) a PhD in a physical or computational science or at least three years of relevant research experience; desirable areas include atmospheric science, computational mathematics, computer science, and physics. Experience with the Unified Model, UKESM or atmospheric modelling is highly desirable but not essential. Experience with simulating climate or chemistry across the recent past is desirable but not essential. Experience interpreting large model datasets or observational datasets using software such as Python, R, or Matlab is essential. Expertise in stratospheric or tropospheric chemistry or aerosol modelling is desirable. Proficiency in Fortran and experience running computer code on high performance computers is desirable.

Anticipated start date for the successful candidate is March 2026. Interviews are likely to be mid February.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload your Curriculum Vitae (CV), a covering letter and publications list in the Upload section of the online application. If you upload any additional documents that have not been requested, we will not be able to consider these as part of your application.

Please quote reference MA48457 on your application and in any correspondence about this vacancy.

The Department holds an Athena SWAN silver award for women in Science, Technology, Engineering, Mathematics, and Medicine.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.