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

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

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CITEEC – Center for Technological Innovation in Construction and Civil Engineering Is the Hosting related to staff position within a Research Infrastructure?NoContact Information Organisation / Company TypeHigher Education Institution WebsiteEmailxesus.nogueira@udc.es State/ProvinceA Coruña Postal Code15071 StreetCampus de Elviña S/NDescriptionDr. 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 – GMNIThe 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 overviewThe 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.Relevant ApplicationsAn 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 environmentThe candidate will be integrated into the , a dynamic research unit with strong international network, within the (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 requirementsSuccessful 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.

5. Language Proficiency:

  • 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 InterestPotential candidates are encouraged to contact Dr. Xesús Nogueira, at . They should include in their email a CV and a short motivation letter.Share this page

Expected salary

Location

A Coruña

Job date

Sat, 24 May 2025 05:56:26 GMT

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