Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Portugal
- United Kingdom
- Germany
- France
- Sweden
- Netherlands
- Spain
- Belgium
- Poland
- Norway
- Denmark
- Singapore
- Italy
- Switzerland
- United Arab Emirates
- Australia
- Morocco
- Finland
- Romania
- Luxembourg
- Czech
- Austria
- Lithuania
- Macau
- Canada
- China
- Estonia
- Brazil
- Ireland
- Greece
- Japan
- Croatia
- Cyprus
- Taiwan
- Vietnam
- Andorra
- Hong Kong
- Israel
- Latvia
- Mexico
- Worldwide
- Europe
- India
- Malta
- Sao Tome and Principe
- Saudi Arabia
- Slovenia
- 38 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Biology
- Science
- Materials Science
- Mathematics
- Chemistry
- Business
- Education
- Environment
- Electrical Engineering
- Earth Sciences
- Arts and Literature
- Psychology
- Law
- Physics
- Humanities
- Linguistics
- Social Sciences
- Philosophy
- Sports and Recreation
- Statistics
- 14 more »
- « less
-
Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 9 days ago
, based on the simulated microstructures. The ATALANTE project, of which this PhD is a part, is divided between experimentation, modeling, and commercialization, and brings together five partners: CEMEF
-
, and supporting training activities, preferable in health science education or higher education setting. · Management and programming of simulation models highly desirable Preferred License: Yes If yes
-
. Teaching skills. Other qualifications: Experience with high-fidelity simulations (DNS, LES). Experience with heat-transfer modeling, especially in complex-geometry flows. Experience with RANS model
-
methods for multiphase flow models Integrate experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase
-
, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty and
-
specimens. The postdoc will contribute to the development of hybrid modeling and identification approaches that combine classical constitutive frameworks, numerical simulation, and machine learning. The work
-
geomatics, spatial modelling and simulation, and model exploration and evaluation (OpenMole platform https://openmole.org/ ). The recruited individual will also work directly with the project's entomologists
-
machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work with
-
of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
-
Keen to push the frontiers of multiphase reactor modeling and accelerate the scale-up of emerging net-zero technologies? Join us at the Department of Chemistry and Chemical Engineering! About us Our