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  Generative learning-enabled digital twins and predictive modelling for ocean sustainability


   Research

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  Dr Shagufta Henna, Dr Salem Gharbia, Dr Eoghan Furey  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The Postgraduate Research Programme COAST offers 12 PhD research scholarships to commence in 2024. Each project will include an enterprise placement of minimum 12 weeks duration.

Marine environments face pollution from waste, chemicals, oil spills, invasive organisms, and other elements. Additionally, the destruction of marine habitats, such as coral reefs and mangroves, poses threats to marine species. Overfishing contributes negatively to ocean acidification, and circulation pattern anomalies, and adversely impacts global seafood production and climate change. Recently, the UN declared a state of oceanic emergency, emphasizing the need to scale up ocean actions through innovative solutions.

Recent efforts aim to improve ocean sustainability by leveraging wireless sensor networks and Artificial Intelligence (AI). In this context, Digital Twins hold the potential to revolutionize ocean sustainability. However, several barriers impede the implementation of Digital Twins and predictive modeling for advancing ocean sustainability. A primary obstacle is the unavailability of quality data, attributed mainly to the challenges in deploying a large-scale sensing, communication, and computational environment, especially for hundreds of large marine ecosystems.

To overcome these challenges, this project aims to design and develop Deep Generative AI Approaches for generating or augmenting data related to fundamental oceanic processes/phenomena. These approaches will be integrated into Digital Twins and other Deep Learning models to support various applications, including reducing overfishing, predicting marine pollution, adapting to climate change, and facilitating marine spatial planning.

Objectives of the research project

  1. Explore the potential of Digital Twins and Deep Generative AI to revolutionize innovative approaches to ocean sustainability.
  2. Develop Deep Generative AI Approaches to generate and augment data related to fundamental oceanic processes and phenomena.
  3. Devise and implement Digital Twins of limited extent for high-priority aquatic zones, such as large marine ecosystems, integrated with Deep Generative AI, to address climate change and facilitate marine spatial planning.
  4. Integrate Generative AI Approaches into Deep Learning models to reduce overfishing and predict marine pollution.

A minimum of 2.1 honours degree (Level 8) in a relevant discipline.

Project Duration:

48 months (PhD)

Preferred Location:

ATU Donegal, Letterkenny Campus

Applications:

Application Form / Terms of Conditions can be obtained on the website: https://www.atu.ie/TU-RISE

The closing date for receipt of applications is 5pm, (GMT) Monday 22nd April, 2024.

Only selected applicants will be called for an online interview (shortlisting may apply).

Environmental Sciences (13)

Funding Notes

TU RISE is co-financed by the Government of Ireland and the European Union through the ERDF Southern, Eastern & Midland Regional Programme 2021- 27 and the Northern & Western Regional Programme 2021-27.
Funding for this Project includes:
• A student stipend (usually tax-exempt) valued at €22,000 per annum
• Annual waivers of postgraduate tuition fee
• Extensive research training programme
• Support for travel, consumables and dissemination expenses

References

Essential Qualifications and Skills: Minimum 2.1 honours degree in Computer Science, Engineering, IT, Mathematics or related field.

Desired skills: Proficiency in Python, or any other programming languages, Background in AI, machine learning, or computer vision, strong analytical skills with knowledge of statistical analysis, excellent written and verbal communication skills, ability to work independently and in multidisciplinary teams.