Fully Funded Climate+Computing PhD — Data, Models & HPC

University of Galway

Ireland

In loco

EUR 23.000 - 28.000

Tempo pieno

10 giorni fa

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Vantaggi offerti da questo lavoro

Fully funded PhD
Fees fully covered
Tax-exempt stipend €25,000 p.a.

Descrizione del lavoro

University of Galway invites applications for a full-time funded PhD scholarship affiliated to the Irish Centre for High-End Computing (ICHEC) and the School of Computer Science. The PhD is part of the Climate + Co-Centre across Ireland, Northern Ireland and Great Britain, and funded by Research Ireland, DAERA and UKRI.

The successful candidate will work under Dr. Paul Nolan with co-supervision at the School of Computer Science, contributing to climate data provisioning and model-based

Competenze

  • Strong MSc/MA in a relevant field and an ambitious, creative mindset.
  • Experience with solving complex computational problems is desirable.
  • Programming, machine learning and large-scale data processing skills are desirable.

Mansioni

  • Support and enable research across the Co-Centre through collaboration with partners.
  • Develop and provide large climate datasets and derived products.
  • Contribute to downscaling regional climate projections using regional models.

Conoscenze

Programming
Machine Learning
Large Scale Data Processing

Formazione

MSc/MA in Computer Science/Physics/Mathematics/Environmental/Climate Science or related

Strumenti

WRF
ICON
MPAS-RCM

Descrizione del lavoro

University of Galway invites applications for a full-time funded PhD scholarship affiliated to the Irish Centre for High-End Computing (ICHEC) and the School of Computer Science. The PhD is part of the Climate + Co-Centre across Ireland, Northern Ireland and Great Britain, and funded by Research Ireland, DAERA and UKRI.

The successful candidate will work under Dr. Paul Nolan with co-supervision at the School of Computer Science, contributing to climate data provisioning and model-based

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