Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Portugal
- United Kingdom
- France
- Germany
- Sweden
- Norway
- Netherlands
- Poland
- Singapore
- Spain
- Belgium
- Denmark
- Italy
- Australia
- Finland
- United Arab Emirates
- Austria
- Czech
- Romania
- Switzerland
- Ireland
- Estonia
- Luxembourg
- Japan
- Morocco
- China
- Canada
- Latvia
- Brazil
- Greece
- Lithuania
- Andorra
- Croatia
- Cyprus
- Hong Kong
- Israel
- Iceland
- India
- Mexico
- Slovenia
- Taiwan
- Vietnam
- Europe
- Malta
- Sao Tome and Principe
- Saudi Arabia
- Slovakia
- 38 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Biology
- Science
- Materials Science
- Mathematics
- Business
- Chemistry
- Education
- Electrical Engineering
- Psychology
- Earth Sciences
- Environment
- Law
- Arts and Literature
- Physics
- Linguistics
- Humanities
- Social Sciences
- Philosophy
- Sports and Recreation
- 13 more »
- « less
-
materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
-
Posting Summary Logo Posting Number RTF00052PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
-
for seasonal prediction using hybrid physics-machine learning models in R&D item Research on Seasonal Meteorological and Oceanographic Forecast Simulator under Development of Integrated Simulation Platform
-
-informed models simulating system behaviour and providing decision-relevant insights Translating methods into decision-support prototypes and case studies in collaboration with academic and industrial
-
numerical models to improve the simulation of complex multiphase phenomena. The study will combine theory, algorithm development, and computational modeling, with the goal of advancing scalable hybrid
-
-world datasets. The core responsibility is to build and validate federated causal inference algorithms through simulations and live demonstrations. Key Responsibilities Participate in and manage the
-
, graph neural networks, physics-informed ML) to approximate PF results Train models using simulation results generated from conventional power flow solvers Evaluate AI-based approximators in terms
-
topics such as statistics, high performance programming, machine learning and using data to constrain cosmological models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
-
Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
research task is to model semantic change and conceptual structure using Natural Language Processing. We will build customized NLP pipelines for premodern Greek and humanistic Latin, train and evaluate word
-
. The research will investigate how phase distribution and flow velocities influence fluid–structure interaction (FSI) and will focus on developing novel sub-models for coupled CFD–FEM simulations. Your tasks