Hosting offer for MSCA PF 2025 at University of A Coruña. Numerical Methods

euraxess.ec.europa.eu - Jobboard; España; Presencial; EUR 30.000 - 42.000; Jornada completa

Descripción de la vacante

La Universidad de A Coruña busca investigadores postdoctorales excepcionales para un proyecto en la intersección de la mecánica de fluidos y métodos numéricos avanzados. Los candidatos deben tener un doctorado en disciplinas relacionadas y experiencia en CFD, y se les brinda apoyo para la presentación de solicitudes competitivas a becas de investigación.

Servicios

Apoyo en la preparación de solicitudes de becas

Red internacional de investigadores

Formación

• Experiencia demostrable en la teoría y aplicación de CFD.
• Experiencia práctica con métodos numéricos para PDEs es altamente deseable.
• Inglés fluido (oral y escrito) es necesario.

Responsabilidades

• Desarrollar métodos innovadores para CFD utilizando técnicas matemáticas avanzadas.
• Integrar técnicas de inteligencia artificial para mejorar los métodos de CFD.
• Trabajar en un entorno de investigación colaborativa.

Conocimientos

Análisis

Solución de problemas

Programación en Python

Comunicación científica

Educación

PhD en Ingeniería, Física, Matemáticas Aplicadas, Informática

Herramientas

Fortran

C++

Descripción del empleo

CITEEC - Center for Technological Innovation in Construction and Civil Engineering

Organisation / Company University of A Coruña Department Applied Mathematics Laboratory CITEEC - Center for Technological Innovation in Construction and Civil Engineering Is the Hosting related to staff position within a Research Infrastructure? No

Dr. Xesús Antón Nogueira Garea is seeking exceptional researchers who hold a PhD (with no more than 8 years of full-time equivalent research experience) and are interested in pursuing a research project within his team in the framework of the Marie Curie Postdoctoral Fellowships 2025 .

Research Group - GMNI

The Group of Numerical Methods in Engineering (GMNI) is specialized in applying computational mechanics techniques to solve large engineering problems (coupled problems of solid mechanics, fluid dynamics, electromagnetism, advection-diffusion problems, bioengineering, etc.) developing the mathematical approach, the numerical formulation, the computer implementation and the numerical simulation and output data postprocessing.

Project overview

The proposed project may target the creation of innovative meshless methods for CFD, emphasizing high accuracy (1), compact stencils (2), robustness with shock waves (3), p- and hp-refinement capabilities (4), suitability for turbulent flows (5), and adaptability to varied geometries and large deformations (6).

This project will develop a novel meshless fluid dynamics method based on Riemann solvers, replacing the traditional use of artificial viscosity in SPH. Riemann problems will be solved between particles, with Moving Least Squares (MLS) approximations used to reconstruct states and compute fluxes efficiently.

The method will integrate the MOOD paradigm to handle shocks with minimal dissipation, applying local, a posteriori corrections. It will also introduce p- and hp-refinement to SPH-like codes—an innovation in this context.

For turbulence, the project will adopt an Implicit Large-Eddy Simulation (ILES) approach, using ADA and energy-based criteria to adapt numerical viscosity dynamically.

This “no model” strategy will be well suited to compressible turbulence in aeronautics, enabling better capture of acoustic and entropy fluctuations. Machine learning techniques will also be explored to enhance accuracy and computational performance.

An interdisciplinary approach is highly feasible and integral to this project. The primary interdisciplinary connection lies in the application of Machine Learning (ML) techniques (from Computer Science/AI) to enhance the CFD methods developed. This involves exploring ML for optimizing parameters, improving closure models, or accelerating computations within the novel meshless framework. Furthermore, the project inherently intersects with:

• Aerospace Engineering: Due to the focus on compressible turbulence, aeronautical applications, and flow phenomena relevant to aircraft and spacecraft.

• Applied Mathematics: The development and analysis of numerical methods (meshless schemes, Riemann solvers, high-order approximations) are core mathematical activities.

• Physics: Specifically, fluid dynamics, which provides the foundational principles for the flows being simulated.

• High-Performance Computing (HPC):** Advanced CFD simulations, especially for turbulent flows, often require significant computational resources and parallel computing expertise.

Fellowship environment

The candidate will be integrated into the Group of Numerical Methods in Engineering , a dynamic research unit with strong international network, within the CITEEC (Technological Innovation Centre in Construction and Civil Engineering) at the University of A Coruña (UDC). The fellow will also receive tailored support in preparing a competitive MSCA Postdoctoral Fellowship application from the Talent Recruitment Office at UDC.

Candidate's requirements

Successful candidates should ideally meet the following requirements:

1. Eligibility / Career Stage:

• Candidates must not have more than 8 years of postdoctoral research experience

2. Educational Background:

• PhD in Engineering, Physics, Applied Mathematics, Computer Science, or a closely related discipline.

3. Experience:

• Essential: Demonstrable experience in Computational Fluid Dynamics (CFD) theory and application.
• Highly Desirable: Practical experience with numerical methods for Partial Differential Equations (PDEs). Familiarity with programming for scientific computing (Fortran, C++, Python).
• Advantageous: Prior exposure to meshless methods, Riemann solvers, turbulence modeling (especially LES or ILES concepts), high-performance computing (HPC), or Machine Learning applications in engineering.

4. Skills:

• Strong analytical and problem-solving skills.
• Ability to work independently and to critically review scientific literature.
• Good programming skills and a willingness to develop complex numerical codes.
• Good communication and scientific writing skills.
• Command of English (both written and spoken) is required for effective scientific communication, reading international literature, writing publications, and presenting research findings.

Other relevant comments for the candidate selection

• Motivation and Research Interest: Candidates should demonstrate a strong motivation and a genuine, proactive interest in the specific research topics outlined in the project description.

• Proactive and Collaborative Spirit: We value candidates who are proactive, intellectually curious, and capable of contributing positively to a collaborative research environment within the Numerical Methods in Engineering group (GMNI)

• Long-term Vision: We are looking for candidates who are enthusiastic about pursuing cutting-edge research and are committed to making significant contributions to the field of computational mechanics.

Expressions of Interest

Potential candidates are encouraged to contact Dr. Xesús Nogueira, at [e-mail] . They should include in their email a CV and a short motivation letter.