AOPP Summer Internships

2018 Summer Programme

Atmospheric, Oceanic and Planetary Physics hosts a research internship programme for undergraduate students during the summer. Students work with a supervisor in the Department, usually a postdoctoral researcher or lecturer, on a self-contained research project. Students are also encouraged to take part in Departmental life, joining researchers for coffee, discussions and seminars. We anticipate taking about six students.

The projects run for up to 10 weeks, nominally from late June to August, though the duration may be shorter to accommodate summer travel. Students are paid a living wage for their time, around £300 per week. The project is full-time but hours can be discussed with your supervisor. Please note that projects are not available to applicants that require a work permit.

To apply for a project please email a CV, name and contact details for one academic reference, and a short covering letter explaining your interest in that placement to the email address given in the project description. Applications will be reviewed as received until the positions are filled.


Cleaning of the atmosphere by anvil clouds Position filled

The most uncertain component of our changing climate remains the interaction of clouds with particulates in the atmosphere (known as aerosols). Anvil clouds, produced by the vigorous convection associated with thunderstorms, extend to the base of the stratosphere and cycle through significant volumes of air. Aerosols in that air become nuclei for water condensation. As those precipitate, the anvil should "clean" the air it encounters.

Measurements of aerosol across Europe and Africa are generated every 15 minutes from a geostationary satellite by researchers in Oxfordshire. This project will use that data to identify anvil clouds and then quantify the change in aerosol loading as they form and travel. A skilled student could also evaluate the impact on the Earth's radiation budget (and, therefore, the climate).

Skills Required

This project would suit a student with experience in using mathematics to analyse large data sets. An understanding of basic statistics is essential. A familiarity with scientific Python, IDL, or similar is preferred.

How to Apply

Supervisors: Prof. Don Grainger and Dr. Adam Povey

Contact: Dr. Adam Povey (adam.povey AT