ORGANISATION/COMPANYJožef Stefan Institute
RESEARCH FIELDComputer science › Programming
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE25/04/2017 23:00 - Europe/London
LOCATIONSlovenia › Ljubljana
TYPE OF CONTRACTTemporary
HOURS PER WEEK40
OFFER STARTING DATE01/09/2017
EU RESEARCH FRAMEWORK PROGRAMMEH2020 / Marie Skłodowska-Curie Actions
MARIE CURIE GRANT AGREEMENT NUMBER722734
The candidate will work on the efficient computational methods for worst-case and multi-level optimisation under the UTOPIAE (Uncertainty Treatment and OPtimisation In Aerospace Engineering) project.
- UTOPIAE will be the first training network that addresses the challenge of finding the ideal compromise between enhancing reliability and safety and educing resource utilisation. UTOPIAE will build upon the existingtheoretical and practical developments in the areas of Uncertainty Quantification (UQ) and Optimisation and will incorporate elements of past and current EU and non-EU projects with the inclusion of Stanford University and partners that are in UMRIDA.
- From the control of manufacturing processes to air traffic management, from decision making on multi-phase programmes to space situational awareness, UQ plays a key role to deliver reliable solutions. At the same time optimised solutions have become a necessity and optimisation is now an essential tool to handle the complexity of our world. Different sectors and communities, deal with uncertainties and optimisation in different forms often equivalent or complementary. Even more interesting is the fine line separating sensitivity analysis and stochastic optimisation. UTOPIAE will look into all these similarities and, by promoting cross fertilisation, will exploit the intimate relationship between optimisation and UQ to make Optimisation Under Uncertainty (OUU) tractable. UTOPIAE consists of 15 PhD projects. JSI leads the ESR11 on the Efficient Computational Methods for Worst-case and Multi-level Optimisation.
- Objectives: To investigate efficient methods and algorithms for worst-case and multi-level optimisation; To develop algorithms that are optimal on expensive problems in Optimisation Under Uncertainty; To test these methods in the applications developed;
- Expected Results: A new set of optimisation algorithms, for the efficient solution of multi-level problems. Implementation of a new set of problem instances of multi-level optimisation. Evaluation framework with defined measures and classifying definitions targeting problems of robust optimisation and reliability-based optimisation.
- Planned secondments: ESTECO (M12-14) to work on the use of the proposed optimisation techniques to reliability based optimisation, Ghent (M24-26) to work on the coupling of the optimisation techniques with uncertainty propagation through dynamical systems.
REQUIRED EDUCATION LEVELComputer science: Master Degree or equivalentPhysics: Master Degree or equivalentMathematics: Master Degree or equivalent
REQUIRED LANGUAGESENGLISH: Excellent
Candidates applying for the PhD position must hold Master's degree in a relevant field and the recruited candidate is expected to enrol as an PhD student at Jožef Stefan International Postgraduate School.
EURAXESS offer ID: 157205
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