Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Germany
- Netherlands
- Spain
- Portugal
- France
- Singapore
- United Arab Emirates
- Norway
- Denmark
- Belgium
- China
- Switzerland
- Australia
- Austria
- Luxembourg
- Canada
- Finland
- Poland
- Hong Kong
- Italy
- Morocco
- Ireland
- Vietnam
- Romania
- Czech
- Japan
- Estonia
- Greece
- Brazil
- Saudi Arabia
- Croatia
- Lithuania
- Andorra
- Cyprus
- India
- South Africa
- Taiwan
- Malta
- New Zealand
- Slovenia
- Worldwide
- Israel
- Kenya
- 36 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Science
- Biology
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Earth Sciences
- Arts and Literature
- Chemistry
- Environment
- Social Sciences
- Humanities
- Linguistics
- Electrical Engineering
- Law
- Sports and Recreation
- Physics
- Philosophy
- Design
- Statistics
- 15 more »
- « less
-
comfort throughout the year in a Nordic climate? Is it possible to predict dynamic outdoor thermal comfort with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead
-
University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 3 hours ago
degrees in educational leadership, marine biology, nursing practice and psychology; and many distance learning options, including clinical research, an accelerated RN-to-BSN program, an Executive M.B.A
-
engineering/M2) to have a solid background in applied mathematics, Machine/Deep Learning, in particular generative models (diffusion models, flow matching), as well as in statistical signal/image processing and
-
implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned
-
machine learning to model network behavior from real-world measurements (e.g., [7]). Although promising, these approaches still face three major limitations: (i) they often rely on idealized and extensive
-
factors: Previous experience in the construction industry; Previous experience in Building Information Modelling; Previous experience in AI and machine learning; Previous experience in process and facility
-
/ThreeBodyTB.jl), cluster expansion, classical potential development, and machine learning. In addition to work on specific problems, I work on developing new first principles-based modeling approaches, including
-
databases. Design, implementation, and testing of deep learning and AI algorithms for processing tabular, genomic and temporal data. Where to apply Website https://www.uam.es/uam/investigacion/ofertas-empleo
-
machine learning Data analysis and advanced statistics Economic and social transformations related to digitization Experince when it comes to programming (preferably Phyton) and in the use of modern tools
-
market using data available on online recruiting platforms, deploying state-of-the-art approaches in Natural Language Processing, Semantic Web, and Agent-based Modeling. For this purpose, an extensive