The International Centre for Numerical Methods in Engineering (CIMNE) is a research centre, created in 1987 by consortium between the Catalan Government and the Universitat Politècnica de Catalunya (UPC-BarcelonaTech), devoted to the development and application of numerical methods to a wide range of areas in engineering. CIMNE has been selected as a Severo Ochoa Centre of Excellence for the period 2019-2023. This is the highest level of recognition of excellence and leadership awarded to a research centre in Spain.
CIMNE is offering a research position that will be funded by the Severo Ochoa Programme.
Number of vacancies: 1
Category: Post Doc Trainee (PDOC2)
Workplace: Madrid
Salary (gross): 31.289,84 EUR
Weekly working hours: Full time
Duration: 2 years
Starting date: No later than Oct 2020
Functions to be developed:
CIMNE is looking for a Postdoc Trainee to be part of the Research and Technical Development (RTD) Group on Machine Learning in Civil Engineering
The functions assigned to the candidate will be:
Requirements:
Other valued skills:
Evaluation procedure:
The requirements and merits will be evaluated with a maximum mark of 100 points. Such maximum mark will be obtained by summing up the points obtained in the following items:
How to apply:
Candidates must complete the "Application Form" form on our website, indicating the reference of the vacancy and attaching the following documents in English:
The deadline for registration to the offer ends on June 14th, 2020 at 12:00 noon.
Application will be reviewed by CIMNE Severo Ochoa selection committee.
The shortlisted candidates may be called for an interview. They may also be required to provide further supporting documentation.
CIMNE is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law. CIMNE has been awarded the HRS4R label.