Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- DAAD
- Nature Careers
- Chalmers University of Technology
- Technical University of Denmark
- Cranfield University
- Forschungszentrum Jülich
- Ghent University
- NTNU - Norwegian University of Science and Technology
- Technical University of Munich
- ; The University of Manchester
- Abertay University
- SciLifeLab
- University of Groningen
- University of Potsdam •
- University of Southern Denmark
- Utrecht University
- ;
- ; Swansea University
- ; University of Sheffield
- ; University of Warwick
- Brandenburg University of Technology Cottbus-Senftenberg •
- Curtin University
- Freie Universität Berlin •
- KNAW
- Leibniz
- University of Bremen •
- University of Twente
- ; Aston University
- ; Technical University of Denmark
- ; University of East Anglia
- ; University of Reading
- ; University of Southampton
- ; University of Surrey
- ; University of Sussex
- Arizona State University
- Colorado State University
- Empa
- Fraunhofer-Gesellschaft
- Heidelberg University
- Heidelberg University •
- Imperial College London
- Julius-Maximilians-Universität Würzburg •
- Justus Liebig University Giessen •
- Karlsruhe Institute of Technology •
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute of Biochemistry •
- Monash University
- Norwegian Meteorological Institute
- Saarland University •
- Swinburne University of Technology
- TU Bergakademie Freiberg
- Trinity College Dublin
- UiT The Arctic University of Norway
- Umeå University
- University of Adelaide
- University of Bonn •
- University of British Columbia
- University of Copenhagen
- University of Göttingen •
- University of Konstanz •
- University of Münster •
- University of Nebraska–Lincoln
- University of Newcastle
- University of Nottingham
- University of Oslo
- University of Stuttgart •
- Universität Hamburg •
- WIAS Berlin
- Wageningen University and Research Center
- 59 more »
- « less
-
Field
-
of data-driven approaches within these multi-parameter models to produce faster and more robust correlations and tools that can be incorporated within industrial methods and have an impact on future designs
-
equations, and numerical methods. Advanced programming skills in languages such as Python, C++, MATLAB, or R. Strong academic curiosity and enthusiasm for the chosen research area. Application Process To
-
in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
-
particular, geomagnetism) and the development of corresponding numerical methods. We offer the opportunity to work in a small interdisciplinary research group consisting of mathematicians, computer (geo
-
: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
-
knowledge of energy system modelling or climate modelling Good knowledge of deep learning, PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary
-
alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
-
computing Advanced knowledge of numerical methods Geophysical fieldwork experience, preferably with GPR, EMI and ERT Strong English writing skills Since the work involves interdisciplinary cooperation with
-
. Experience in implementing numerical methods and algorithms, e.g. in Python, Matlab or similar, is required. A strong motivation to develop mathematical tools for biological and medical applications is
-
environments with minimal environmental impact. We are recognized nationally and internationally for our excellence in numerical and computational modelling, experimental innovations, our collaborations with