Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- NTNU Norwegian University of Science and Technology
- KU LEUVEN
- Wageningen University & Research
- NTNU - Norwegian University of Science and Technology
- ETH Zürich
- Maastricht University (UM)
- SciLifeLab
- ;
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- BRGM
- Centro de Investigaciones sobre Desertificación (CIDE, CSIC-UV-GVA)
- Chalmers University of Technology
- DIFFER
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Forschungszentrum Jülich
- Foundation for Research and Technology-Hellas
- IDAEA-CSIC
- IMEC
- Inria, the French national research institute for the digital sciences
- Institut Agro Rennes-Angers
- Institute of materials and machine mechanics Slovak academy of sciences
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- Luxembourg Institute of Science and Technology (LIST)
- Norwegian University of Life Sciences (NMBU)
- Oxford Brookes University
- Tallinn University of Technology
- Technical University Of Denmark
- Technical University of Denmark
- Technical University of Denmark (DTU)
- Technical University of Munich
- Technological University Dublin
- The University of Manchester
- University of Cambridge;
- University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC)
- University of Groningen
- University of Mainz
- University of Oldenburg
- Università degli Studi di Firenze
- Uppsala universitet
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- Łukasiewicz Research Network - Krakow Institute of Technology
- 33 more »
- « less
-
Field
-
detailed knowledge of the performance parameters that affect their application software, as it aids in making future technology choices, predicting performance and scalability, and adapting critical software
-
for the development of more predictive preclinical platforms. This PhD project is part of the ANR JCJC EXOFLEX project, which aims to develop an instrumented microfluidic platform capable of simultaneously controlling
-
authenticity of visual media and provide understandable evidence for model decisions. The candidate will investigate how general-purpose pretrained visual and multimodal representations can be adapted
-
developing simulation flows, analysis methodologies, and predictive models that enable Design-Technology and System-Technology Co-Optimization (DTCO/STCO) studies for future systems. You will work closely with
-
regularly in its various training and research activities, as well as the weekly seminars in IDAEA-CSIC. Where to apply Website https://www.idaea.csic.es/job-offer/phd-position-understanding-and-predicting-n
-
. This includes extending or adapting existing scenario modelling approaches to support increasingly complex cybersecurity exercises. RO3: Investigate simulation and predictive modelling approaches
-
of the MOST (Modelling and Simulation of Turbulence) team focus on the numerical prediction of turbulent and multiphase flows with a broad range of objectives from fundamental understanding of flow properties
-
interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The
-
rules for ceramic shell mould clusters; Experimental validation of the relationships between microstructure and thermal shock resistance; Development of multi-scale finite element models for predicting
-
at the Laplace laboratory, where numerical and analytical models are being developed to predict plasma potential control and flux entrainment from polarized electrodes. During the third year of the thesis project