CFD Postdoc: Floating Offshore Wind & ML Surrogates

RFCSR

Oxford

On-site

GBP 39,000 - 48,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

RFCSR in Oxford's Department of Engineering Science invites applications for a Postdoctoral Research Assistant in floating offshore wind. The role focuses on high‑fidelity CFD simulations of floating wind turbines, employing actuator‑line models, and on developing data‑driven surrogate models for real‑time aerodynamic loads in experimental setups.

The successful candidate will contribute to machine learning surrogates and hybrid testing methodologies, collaborating within a multidisciplinary

Qualifications

  • A solid background in computational fluid dynamics (CFD) and wind turbine fluid mechanics is essential.
  • Experience with data-driven modelling techniques and high-performance computing will support surrogate model development.
  • Strong analytical skills and the capacity to work collaboratively within a multidisciplinary research group.

Responsibilities

  • Conduct high-fidelity CFD simulations of floating wind turbines using actuator-line methods.
  • Assess applicability of reduced-order models for turbine performance prediction and support development of surrogate models for real-time loads.
  • Collaborate within a multidisciplinary group to advance hybrid testing and understanding of floating offshore wind dynamics.

Skills

CFD
Wind turbine fluid mechanics
Data-driven modelling
High-performance computing
Analytical skills
Team collaboration

Education

PhD (or near completion) in engineering/related

Job description

RFCSR in Oxford's Department of Engineering Science invites applications for a Postdoctoral Research Assistant in floating offshore wind. The role focuses on high‑fidelity CFD simulations of floating wind turbines, employing actuator‑line models, and on developing data‑driven surrogate models for real‑time aerodynamic loads in experimental setups.

The successful candidate will contribute to machine learning surrogates and hybrid testing methodologies, collaborating within a multidisciplinary

Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

Postdoctoral Research Assistant in Floating Offshore Wind
Postdoctoral Research Assistant in Floating Offshore Wind

RFCSR • Oxford

On-site
GBP 39,000 - 48,000
Postdoc: Offshore Digital Twins for Wind Turbines (Flexible Working)
Postdoc: Offshore Digital Twins for Wind Turbines (Flexible Working)

Times Higher Education • Cranfield

Hybrid
GBP 35,000 - 43,000
Research Associate for Machine Learning Modelling for Next-Level Fast Nonlinear Wave-Structure Interaction
Research Associate for Machine Learning Modelling for Next-Level Fast Nonlinear Wave-Structure Interaction

The University of Manchester • Manchester

Hybrid
GBP 36,000 - 52,000
Pension scheme
Health and wellbeing services
Annual leave & holidays
+3
Early Stage Researcher: Offshore Wind Data Science & ML
Early Stage Researcher: Offshore Wind Data Science & ML

University of Warwick • Coventry

Hybrid
GBP 36,000 - 44,000
Pension scheme
Holiday entitlement
Parental/adoption leave
+3
Research Associate for Machine Learning Modelling for Next-Level Fast Nonlinear Wave-Structure Inter
Research Associate for Machine Learning Modelling for Next-Level Fast Nonlinear Wave-Structure Inter

Diversity Dashboard • Manchester

Hybrid
GBP 34,000 - 52,000
Pension scheme
Employee health services
Annual leave
Research Associate for Machine Learning Modelling for Next-Level Fast Nonlinear Wave-Structure [...]
Research Associate for Machine Learning Modelling for Next-Level Fast Nonlinear Wave-Structure [...]

The University of Manchester • Manchester

Hybrid
GBP 38,000 - 46,000
Pension scheme
Health and wellbeing services
Generous annual leave
+2
Hybrid Offshore Digital Twins Research Fellow
Hybrid Offshore Digital Twins Research Fellow

Cranfield University • Cranfield

On-site
GBP 35,000 - 43,000
Flexible working options
Disability Confident Employer
Family-friendly employer
Research Fellow in Offshore Digital Twins
Research Fellow in Offshore Digital Twins

Times Higher Education • Cranfield

Hybrid
GBP 35,000 - 43,000
Research Associate: Nonlinear Wave ML for Floating Platforms
Research Associate: Nonlinear Wave ML for Floating Platforms

The University of Manchester • Manchester

Hybrid
GBP 38,000 - 46,000
Pension scheme
Health and wellbeing services
Generous annual leave
+2
Research Fellow in Offshore Digital Twins
Research Fellow in Offshore Digital Twins

Cranfield University • Cranfield

On-site
GBP 35,000 - 43,000
Flexible working options
Disability Confident Employer
Family-friendly employer