Funding

Self-funded

Project code

COMP6381025

Department

School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Farzad Arabikhan, Dr Becky Canning and Dr David Hutchinson.

The work on this project could involve:

  • Generating the 3D air quality topology of the International Port of ºÚÁϳԹÏ(PIP)  using environmental drones equipped with air quality sensors
  • Collecting real time data and modelling air quality in different scenarios of PIP decarbonisation in conjunction with the existing digital twins
  • Using optimisation and machine learning methods to predict and recommend the most efficient scenarios and strategies for reducing PIP air pollution

Context

Decarbonising ports presents a significant challenge in the transition to net zero, as an example of multi-modal transport hubs with multiple users and complexities. ºÚÁϳԹÏInternational Port is taking an active lead through shore side power solutions, and the 4.5 year SEA CHANGE project will provide a portside solution to emissions reduction. This PhD will work alongside industry partners (ºÚÁϳԹÏInternational Port, Brittany Ferries, Iotics, B4T) and multiple academics from across the university over the 3 year demonstrator phase of the £23M project, enabling you to help deliver actionable solutions to the maritime problem.

This proposal outlines a project focuses on utilising environmental drones equipped with air quality sensors  to create 3D heat and topography map of air quality for the ºÚÁϳԹÏInternational Port. This will provide valuable insight into the spatial distribution of pollutants considering factors such as ships arrival, berthing and leaving as well as other equipment, machines and vehicles inside the port . The main objectives of this project are as follows:

  • To conduct multiple drone flights over the international port, capturing real-time air quality data during each flight and geo-reference all collected data to create a spatial database for further analysis
  • To collect data from environmental drones and integrate it with the existing fixed-location sensors and digital twin to comprehensively assess and map air quality within and around the ºÚÁϳԹÏInternational Port 
  • To capture variations and hotspots of key air pollutants considering ships traffic flows and understand their impact on the surrounding environment.
  • To identify spatial patterns and variations in air quality in different port's decarbonisation scenarios 
  • To use machine learning and spatial modelling techniques to model air quality within the port area in different decarbonisation scenarios 
  • To contribute to the development of strategies for air quality improvement and environmental sustainability within the port area.

Funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

 

 

 

 

We are seeking a highly motivated and qualified Ph.D. candidate. A strong background in computer knowledge and programming skills (Python, Java or C/C++).

 

How to apply

We’d encourage you to contact Dr Farzad Arabikhan (farzad.arabikhan@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process.

When applying please quote project code: COMP6381025