Back to search results

PhD Studentship: Paleo-modelling of the Red Sea

The University of Manchester

Qualification Type: PhD
Location: Manchester
Funding for: UK Students, EU Students, International Students
Funding amount: £18,622
Hours: Full Time
Placed On: 9th January 2024
Closes: 28th April 2024

This is a 3.5 year PhD Studentship  which will cover fees and stipend set at the UKRI rate (£18,622 in 2023/24). This project is open to UK residents and EU residents who have settled status or pre-settled status.

The successful candidate will have a good degree in mathematics, physics, engineering, environmental sciences, or similar, with good understanding of fluid mechanics and mathematical models of physical systems.

The project is suited to someone with strong mathematical and modelling skills, interested in developing their understanding of oceanographic flows and biogeochemical processes.

The Red Sea is a semi-enclosed basin, with limited connections to the open ocean, with narrow and shallow straits operating a strong control on exchanges between the Red Sea and the wider ocean.  Currently the Red Sea is dominated by evaporation, leading to saline conditions, with dense saline waters descending into the deep water and keeping the deeper waters oxygenated.  However, the Red Sea has experienced changes in sea level, atmospheric forcing (winds, precipitation), insolation, and tectonic changes in basin configuration and sill geometry, leading to different circulation patterns.

Evidence of past climates can be obtained from drill cores, showing, for example, periods of organic-rich layer formation, indicating the deep waters were relatively stagnant and de-oxygenated for periods in the past, as well as giving information about past salinities and temperatures.  This in turn will have resulted from different forcing and/or topography.  The interpretation of the geological record requires an understanding of the relation between the record and the basin conditions.

You will work in an interdisciplinary team, including paleoceanographers from Earth & Environmental Sciences, who investigate and interpret the geological record, and fluid dynamicists from the Department of Fluids and Environment, expert in numerical and mathematical modelling of ocean flows and processes. The project will focus on developing mathematical models capturing the key physical and biogeochemical processes in the past, present and future Red Sea, in order to identify the key parameters that control the observed geological record.  The modelling will include mathematical models of multi-layer hydraulic control at straits, simple box models representing fluxes of heat and salt; models representing geochemical processes that lead to sedimentation and deoxygenation; and numerical models of wind-driven circulation and eddy formation.  Combining the improved representation of oceanic processes with information from the geological record will enable us to improve our understanding of past and future climates and impacts.

We strongly recommend that you contact the supervisor(s) for this project before you apply; The Email addresses for Dr Gregory Lane-Serff, Dr Neil Mitchell and Dr David Apsley are Gregory.F.Lane-Serff @manchester.ac.uk, Neil.Mitchell@manchester.ac.uk and David.apsley@manchester.ac.uk

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):

Location(s):

PhD tools
 

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Ok Ok

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Manage your job alerts Manage your job alerts

Account Verification Missing

In order to create multiple job alerts, you must first verify your email address to complete your account creation

Request verification email Request verification email

jobs.ac.uk Account Required

In order to create multiple alerts, you must create a jobs.ac.uk jobseeker account

Create Account Create Account

Alert Creation Failed

Unfortunately, your account is currently blocked. Please login to unblock your account.

Email Address Blocked

We received a delivery failure message when attempting to send you an email and therefore your email address has been blocked. You will not receive job alerts until your email address is unblocked. To do so, please choose from one of the two options below.

Max Alerts Reached

A maximum of 5 Job Alerts can be created against your account. Please remove an existing alert in order to create this new Job Alert

Manage your job alerts Manage your job alerts

Creation Failed

Unfortunately, your alert was not created at this time. Please try again.

Ok Ok

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

 
 
 
More PhDs from The University of Manchester

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended

jobs.ac.uk has been optimised for the latest browsers.

For the best user experience, we recommend viewing jobs.ac.uk on one of the following:

Google Chrome Firefox Microsoft Edge