Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Portugal
- Netherlands
- Germany
- France
- Sweden
- Spain
- Belgium
- Denmark
- Norway
- Italy
- Singapore
- Finland
- Australia
- Morocco
- Switzerland
- Czech
- Poland
- United Arab Emirates
- Canada
- China
- Ireland
- Luxembourg
- Austria
- Romania
- Japan
- Estonia
- Hong Kong
- Brazil
- Vietnam
- Andorra
- Bulgaria
- Croatia
- Greece
- Hungary
- Lithuania
- Malta
- Saudi Arabia
- Slovenia
- 30 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Environment
- Business
- Psychology
- Humanities
- Linguistics
- Physics
- Arts and Literature
- Electrical Engineering
- Law
- Social Sciences
- Education
- Philosophy
- Sports and Recreation
- Statistics
- 14 more »
- « less
-
to pre-train a common GNN backbone model capable of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a
-
, aimed at revolutionizing the way osteoarthritis is understood, diagnosed and treated by developing multimodal patient-relevant endpoints, advanced predictive models, and next-generation clinical trial
-
CORE A*/A conference paper. We invite applications for a postdoctoral position focused on the development of predictive models for clinical outcomes following Deep Brain Stimulation (DBS) in Parkinson’s
-
-0831 Description of Work: At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents
-
network performance data obtained from user devices. Assist in the development of basic models to predict or explain network behaviour under different conditions. Contribute to the improvement of internal
-
postdoctoral researcher position in theoretical cosmology. The position is dedicated to developing a robust and efficient framework that incorporates a broad range of neutrino and dark-matter models, assessing
-
imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
-
, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
-
network performance data obtained from user devices. Assist in the development of basic models to predict or explain network behaviour under different conditions. Contribute to the improvement of internal
-
particle formation for atmospherically relevant molecules. ORCTOOL (Organic Cluster Tools) aims to create a toolbox for understanding and cost-effectively predicting the rate of massively multicomponent