closed job offers

VAC-2022-93 – Reduced-Order Modelling of Fibre-reinforced structural devices

Published: 20/12/2022


Number of places: 1

Category: Post Doc 1

Workplace: C2

Salary (gross): 38.884,97€

Weekly working hours: 40

Duration: 6 months

Function to be developed:

Research activity dealing with the parametrization of Fibre-Reinforced Concrete devices (stating the problem, geometry, loads, boundary conditions, outputs of engineering interest…), the resolution with a standard finite element code (Full-Order Models) and its formulation to be solved as a non-intrusive Reduced-Order Model. The exploitation of the Reduced-Order Model as a tool for optimization and uncertainty quantification is the natural outcome of the project but, due to the time limitation of this offer we only expect to create the background necessary.

Required skills:

  • Deep knowledge of the characteristics of Fibre-Reinforced Concrete, in all its different variants, including experience in experimental testing.
  • Numerical Modelling skills
  • Critical and analytical mindset
  • Writing and Communication skills

Other valued skills (not mandatory):

  • Work team
  • Open to international playground

Qualification system:

The requisites and merits will be evaluated with a maximum note of 100 points. Such maximal note will be obtained summing up the following points:

  • Publication and career track: 30%
  • Previous research experience in the field of the position: 30%
  • Programming skills: 20%
  • Language skills: 15%
  • Communication/Teaching skills: 5%

Candidates must complete the "Application Form" form on our website, indicating the reference of the vacancy and attaching the required documents.

The deadline for registration to the offer ends on January 10th, 2023 at 12 noon.

The preselected candidates may be requested to send the documentation required in the "Requirements" and "Merits" sections, duly scanned, and may be called to go through selection tests (which might be of eliminatory nature) and / or personal interviews.

Proyecto de I+D+i PID2020-113463RB-C33, financiado por MCIN/ AEI/10.13039/501100011033/

PLAN DE RECUPERACION