Duration: 2017 – 2021
Funded by: HORIZON 2020
About: UTOPIAE is a training and research network funded by the European Commission hrough the H2020 funding scheme. The main objectives of this network are to train, by research and by example, 15 “Early Stage Researchers” (ESRs) in the field of Uncertainty Quantification (UQ) and Optimization and to impart them the skills to become leading independent researchers and entrepreneurs that will increase the EU innovation capacity. These skills will enable the ESRs to pursue careers in academia and industry. Through individual research projects, each ESR will investigate different facets of UQ and Optimization Under Uncertainty and develop cutting-edge methods and algorithms with particular focus on aerospace applications.

Technology, Arts, Sciences – TH Köln

The SPOTSeven Lab, which is part of the Technische Hochschule Köln, offers the following two ESR positions:

ESR12 Technische Hochschule Köln
Project title: Robust Mixed-integer Optimisation in Uncertain Environments Objectives:
To develop and study evolutionary optimisation methods with regard to mixed-integer problems involving uncertainty; To define a procedure that can efficiently explore large parameter spaces in robust design; To integrate the identified methods in the sequential parameter optimisation toolbox (SPOT); To analyse and develop suitable optimisation methods and parameter settings for efficient optimisation of constraint robust mixed-integer design problems.
Expected Results: Evaluation of different approaches to uncertainty quantification for mixed-integer optimisation problems. Algorithms for the solution of nonlinear mixed-integer problems under uncertainty. Integration into SPOT frame-work of a simplified simulator, a constraint nonlinear mixed-integer optimisation problem, is one expected result. Experimental and theoretical analysis of performance.
Planned Secondments: SU (Month 31-33) to apply MINLP to optimal multi-target tracking with FSS within WP3.2, DLR (M37-39) to apply MINLP to a drag reduction problem within WP3.2.
This position will be supervised by Prof. Dr. Thomas Beielstein and Prof Naujoks.

ESR13 Technische Hochschule Köln
Project title: High Efficiency Many Objective Evolutionary Optimisation MethodsObjectives: To build an effective many-objective optimisation loop for robust optimisation; To identify promising techniques for handling many-objective optimisation tasks for aerospace applications; To identify a framework for integration of techniques for many-objective optimisation of large scale expensive problems; To integrate such methods for large scale robust design optimisation problems from WP3.2 with UQ techniques; To develop a simplified simulator to accelerate the testing/tuning loop in collaboration with CIRA providing simplified simulators based on RANS CFD solvers but using coarser grids etc.; To test the considered techniques on the design of aerospace transportation systems, optimal energy-driven aircraft design and RLV design; Identify most promising approaches capable of handling alternative applications from the project‟s field.
Expected Results: Algorithms for the solution of many-objective expensive problems under uncertainty. Theoretical and experimental analysis of the structure of the problem and performance of the algorithms. Extension of the SPOT frame-work to handle such many-objective, expensive, constrained nonlinear problems. Development and incorporation of a simplified (low-fidelity) simulator as an ideal test case for statistical analysis.
Planned Secondments: Airbus GmbH (M15-17) and CIRA (M31-33) to work on the application of many-objective evolutionary optimisation techniques to the optimal energy-driven aircraft design under uncertainty within WP3.2.
This position will be supervised by Prof. Dr. Thomas Beielstein and Prof Naujoks.

An overview of the employment opportunities can be found here: http://utopiae.eu/employment-opportunities/


Contact: If you would like to ask anything about UTOPIAE, contact us by emailtwitter or visit our webpage.

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This project has received funding from the biggest European Union Research and Innovation Programme Horizon 2020  HORIZON 2020 Website