Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Portugal
- Germany
- Sweden
- Netherlands
- Spain
- Norway
- Belgium
- Italy
- Denmark
- Singapore
- Australia
- Ireland
- Finland
- Switzerland
- Czech
- Austria
- China
- Luxembourg
- Poland
- Canada
- Estonia
- Morocco
- Romania
- United Arab Emirates
- Hong Kong
- Brazil
- Japan
- Andorra
- Macau
- Saudi Arabia
- Vietnam
- Barbados
- Bulgaria
- Iceland
- Latvia
- Lithuania
- Malta
- 30 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Business
- Environment
- Linguistics
- Humanities
- Law
- Psychology
- Electrical Engineering
- Physics
- Arts and Literature
- Social Sciences
- Sports and Recreation
- Education
- Design
- Philosophy
- 14 more »
- « less
-
learning models to predict ion-exchange isotherm parametersIntegration of predicted parameters into the CADET chromatography simulation framework Simulation and analysis of batch and gradient elution
-
of data analytics and mathematical modeling to predict clinically relevant biological outcomes using in vitro engineered tissue systems and in vivo models and will play a central role in the development
-
—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from
-
NIST only participates in the February and August reviews. The fire modeling community is actively working to develop the tools needed to quantitatively predict material and product flammability
-
model introduced previously for carburizing will be further developed in this study. In this model, carbon diffusion is predicted using Fick's law and finite difference scheme. A source term accounts for
-
, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling
-
scraping Training and evaluating ML models Connecting real-time streamed data with predictive models Duties Typical job duties for this position will focus on tasks related to: Collecting historical data
-
) approaches. Design predictive maintenance algorithms using machine learning, statistical learning, and digital twin-based models to anticipate failures and optimise maintenance interventions. Integrate AI
-
physical agent-based models, as well as the integrations of omic information to validate model predictions and developed in the context of the HPC environments at the BSC and at other HPC centres in Europe
-
minimum of 12 months Appointment Start Date: Early/mid 2026 Group or Departmental Website: https://evodesign.org/ (link is external) How to Submit Application Materials: Please directly contact us at