11 PhD positions in an European Industrial Doctorate, extended deadline December 15, 2017

Extended deadline: December 15, 2017

ROMSOC is a European Industrial Doctorate (EID) project in the programme Innovative Training Networks (ITN) and part of Marie Sklodowska Curie Actions within the Horizon 2020 programme. The ROMSOC EID Network brings together 15 international academic institutions and 11 industry partners and supports the recruitment of eleven Early Stage Researchers (ESRs). Each ESR will be working on an individual research project in the host institution with secondments related to their research in other academic and industrial partners of the network. The research is focused on three major topics: coupling methods, model reduction methods, and optimization methods, for industrial applications in well selected areas, such as optical and electronic systems, economic processes, and materials. The ROMSOC EID Network offers a unique research environment, where leading academics and innovative industries will integrate ESRs into their research teams for the training period, providing an excellent structured training programme in modelling, simulation and optimization of whole products and processes.

We seek excellent open-minded and team-spirited PhD candidates who will get unique international, interdisciplinary and inter-sectoral training in scientific and transferable skills by distinguished leaders from academia and industry. Deadline applications: 25 November. The calls for the ESR positions in the ROMSOC project have now been published at the EURAXESS webpage:

11 Early Stage Research Positions available in MSCA-ITN-EID project ROMSOC
(EURAXESS Job Offer id: 257318)
The following positions are available:

RTC implementation of high-performance algorithms for adaptive optics control
Reference number: ROMSOC-ESR01
Johannes-Kepler Universität, Linz, Austria

Mathematical modelling and numerical simulation of coupled thermo-acoustic multi-layer systems for enabling particle velocity measurements in the presence of airflow.
Reference number: ROMSOC-ESR02
ITMATI, Santiago de Compostela, Spain

FreeForm Optics applications of Optimal Transport Solvers
Reference number: ROMSOC-ESR03
INRIA, Paris, France

Data driven model adaptations of coil sensitivities in MR systems.
Reference number: ROMSOC-ESR04
University of Bremen, Bremen, Germany

Coupling of Model Order Reduction and Multirate Techniques for coupled heterogeneous time-dependent systems in an industrial optimization flow.
Reference number: ROMSOC-ESR05
Bergische Universität Wuppertal, Wuppertal, Germany

Model order reduction for parametric high dimensional models in the analysis of financial risk.
Reference number: ROMSOC-ESR06
Technische Universität Berlin, Berlin, Germany and MathConsult GmbH, Linz, Austria

Integrated Optimization of International Transportation Networks.
Reference number: ROMSOC-ESR07
Friedrich-Alexaner Universität Erlangen-Nürnberg, Erlangen, Germany

Efficient computational strategies for complex coupled flow, thermal and structural phenomena in parametrized settings.
Reference number: ROMSOC-ESR08
ITMATI, Santiago de Compostela, Spain

Numerical simulations and reduced models of the fluid-structure interaction arising in blood pumps based on wave membranes.
Reference number: ROMSOC-ESR09
Dipartimento di Matematica, Politecnico di Milano, Milan, Italy

Coupled parameterized reduced order modelling of thermo-hydro-mechanical phenomena arising in blast furnaces.
Reference number: ROMSOC-ESR10
Scuola Internazionale Superiore di Studi Avanzati di Trieste (SISSA), Trieste, Italy

Optimal Shape Design of Air Ducts in Combustion Engines.
Reference number: ROMSOC-ESR11
Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany

Workshop: “Reducing Dimensions and Cost for UQ in Complex Systems Isaac Newton Institute”

Workshop: Reducing Dimensions and Cost for UQ in Complex Systems
Isaac Newton Institute, Cambridge
5 – 9 March 2018

https://www.newton.ac.uk/event/unqw03

Registration for this workshop is open through to January 3, 2018.

Organizers:
Francisco Alejandro Díaz De la O, University of Liverpool, UK, f.a.diazdelao@liverpool.ac.uk
James Gattiker, Los Alamos National Laboratory, gatt@lanl.gov
Gianluigi Rozza, SISSA International School for Advanced Studies Trieste, Italy, gianluigi.rozza@sissa.it
Elisabeth Ullmann, Technical University of Munich, Germany, elisabeth.ullmann@ma.tum.de

Uncertainty quantification (UQ) in complex mathematical models is a huge computational challenge for many reasons. Simple UQ tasks such as the estimation of statistical properties of system outputs often require multiple calls to a deterministic solver. A single solver call is already very expensive for complex mathematical models. Advanced UQ tasks such as sensitivity and reliability analysis, parameter identification, or optimal control and design often involve several layers of increasing complexity where each layer requires the performance of a specific UQ task. This workshop will address efficient numerical and statistical methods for reducing the overall cost of solving discrete problems that arise in UQ studies, focusing on methodologies that reduce the dimension of the problems to be solved.

Talks will be organised around topics such as: multilevel and multifidelity methods; reduced basis methods; dimension reduction strategies; low rank and tensor methods; challenges in Gaussian process emulation, and active subspaces. Workshop speakers and participants will be encouraged to explore connections between these topics. There will also be two contributed poster presentations. Please indicate on the registration form if you are interested in presenting a poster. A limited amount of funding may be available to support PhD students.

Please see the workshop webpage soon updated with a list of speakers and tentative titles, and already updated for registration details.

This workshop is the third event in a six-month programme on Uncertainty Quantification at the Isaac Newton Institute:
https://www.newton.ac.uk/event/unq
Organizers: Peter Challenor (University of Exeter), Max Gunzburger (Florida State University), Catherine Powell (University of Manchester), Henry Wynn (London School of Economics)