PhD in Bias-Aware Data Assimilation for Aeronautics

Imperial Enterprise; Greater London; Presencial; GBP 21.000 - 26.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Fully funded PhD studentship

Descripción de la vacante

Imperial College London is offering a fully funded PhD studentship in Aeronautics to develop bias-aware data assimilation methods that correct model error as dynamics evolve. You will work at the interface of physics, mathematics and computation, using high-performance computing facilities and Bayesian inference techniques. The project spans 3.5 years, with supervision by Dr.

Andrea Nóvoa. A stipend of £23,805 per year (tax-free for Home, EU and International students) supports research and

Formación

• First-class honours in Aeronautics, Mechanical Engineering, Mathematics, Statistics or Physics.
• Background in computational physics or mathematics is advantageous.
• Interest in data assimilation, dynamical systems and multi-physics computation at the physics-mathematics interface.

Responsabilidades

• Develop bias-aware data assimilation methods that learn from data as dynamics evolve.
• Apply Bayesian inference and machine learning within physics-constrained frameworks.
• Present work at international conferences and publish in peer-reviewed journals.

Conocimientos

Data assimilation

Bayesian inference

Physics-constrained ML

High-performance computing

Educación

First-class honours MEng/MSci or international equivalent

Descripción del empleo

Imperial College London is offering a fully funded PhD studentship in Aeronautics to develop bias-aware data assimilation methods that correct model error as dynamics evolve. You will work at the interface of physics, mathematics and computation, using high-performance computing facilities and Bayesian inference techniques. The project spans 3.5 years, with supervision by Dr.

Andrea Nóvoa. A stipend of £23,805 per year (tax-free for Home, EU and International students) supports research and