Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Norway
- France
- United Kingdom
- Portugal
- Netherlands
- Sweden
- Germany
- Denmark
- Australia
- Belgium
- Poland
- Spain
- Austria
- Singapore
- Finland
- Canada
- Ireland
- Italy
- Czech
- Morocco
- Luxembourg
- China
- Romania
- Switzerland
- Japan
- Cyprus
- Estonia
- Latvia
- United Arab Emirates
- Slovakia
- Bulgaria
- Israel
- Lithuania
- Malta
- Mexico
- Andorra
- Bangladesh
- Barbados
- Europe
- Greece
- Hong Kong
- Hungary
- New Zealand
- Saudi Arabia
- Worldwide
- 36 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Materials Science
- Chemistry
- Social Sciences
- Education
- Electrical Engineering
- Earth Sciences
- Psychology
- Arts and Literature
- Humanities
- Environment
- Linguistics
- Law
- Sports and Recreation
- Physics
- Philosophy
- Design
- 14 more »
- « less
-
the GEOSIC project, based on research in geopolitics. We will implement the scenarios developed for the SAI deployment in a climate model coupled with a control module (PID) in order to quantitatively simulate
-
. Designing and implementing semantic mappings from external metadata standards, ontologies, and controlled vocabularies into the HelmholtzKG data model. Building and operating automated data pipelines
-
theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise
-
, affect, and cognitive control — and how disruptions in these processes underlie psychiatric disorders. We use a multimodal approach combining fMRI, pharmacological manipulations, computational modeling
-
environmental geophysics. This PhD project aims to advance the process-based understanding of SSF by combining state-of-the-art geophysical methods with controlled field experiments and numerical modeling
-
for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
-
a large-scale field campaign across ancient forest stands to reconstruct soil ecosystem carbon budgets and develop dynamic models of complex soil ecosystems based on the literature. The goal is to
-
infrastructure (e.g., turbine components). Research on advanced deep learning techniques, including architectures based on GRU, LSTM, attention mechanisms, and hybrid models. Implementation of real-time predictive
-
shaping will be central to the study. The numerical model will be based on the boundary element method (BEM) and semi-analytical approaches developed at I2M. The experimental proof-of-concept will leverage
-
using methods such as Dynamic Mode Decomposition with control (DMDc). You will also assist in the development of predictive control approaches based on reduced-order models, and contribute to workflow