PhD studentship: what does the future hold for European shelf seas ecosystems? 

The University of Exeter’s Centre for Doctoral Training in Environmental Intelligence, in partnership with the UK Hydrographic Office, is inviting applications for a fully-funded PhD studentship to commence in September 2022 or as soon as possible thereafter. 

Application deadline: midnight on 9th June 2022

Location: Mathematics, Streatham Campus, Exeter

Funding: For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £16,062 for 4 years full-time, or pro rata for part-time study

Apply now

Application process:

In the application process you will be asked to upload several documents. 

  • CV
  • Letter of application (outlining your academic interests and expertise, prior research experience and reasons for wishing to undertake the project).
  • Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)
  • Names of two referees familiar with your academic work. You are not required to obtain references yourself. We will request references directly from your referees if you are shortlisted.
  • If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English.

Proposed research:

This project will research the details of processes through which marine ecosystems on the European Shelf are impacted by atmospheric CO2. It will examine how identified changes, their drivers, and feedback mechanisms in turn affect the shelf seas’ biogeochemistry, health, and biodiversity, with special emphasis on the organic and inorganic particle load that changes seawater clarity. Based on the identified changes and drivers, the future evolution of shelf seas’ biogeochemistry will be numerically predicted.

We will utilise existing data, complemented by collecting new observations, together with statistical and high-resolution numerical modelling, as well as machine learning techniques.
Data sources to be utilised that are publicly available include remotely sensed data and reanalysis data, and in-situ observations.

Remotely sensed and reanalysis data can be used to identify ocean surface chlorophyll concentrations (a proxy for phytoplankton activity), coloured dissolved organic matter (CDOM; an indicator of organic matter), as well as particulate matter, temperature, salinity, ocean currents, wind speed, etc.

Applying statistical modelling and machine learning techniques, we will identify hindcasts of the drivers of marine ecosystem variability, utilising these data.

Existing in-situ observations will be used to validate any resulting drivers; depending on field-work regulations, we are hoping to be able to enhance the in-situ observational datasets by collecting and analysing additional samples for relevant parameters.

Additionally, we will utilise a high-resolution coastal biogeochemical model to study the processes driving change. Finally, using all obtained results and understanding, we will use predictive modelling to identify potential shelf sea ecosystem conditions in decades to come. 

University of Exeter, 25 May 2022. More information.


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