Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Singapore
- Australia
- Germany
- Netherlands
- France
- Spain
- Sweden
- Austria
- United Arab Emirates
- Portugal
- Norway
- Belgium
- Denmark
- Canada
- China
- Italy
- Switzerland
- Czech
- Ireland
- Poland
- Finland
- Morocco
- Romania
- Hong Kong
- Luxembourg
- Cyprus
- India
- Japan
- South Africa
- New Zealand
- Saudi Arabia
- Taiwan
- Armenia
- Barbados
- Croatia
- Estonia
- Kyrgyzstan
- Latvia
- Lithuania
- Malta
- Slovenia
- Vietnam
- 34 more »
- « less
-
Program
-
Field
- Computer Science
- Economics
- Medical Sciences
- Business
- Engineering
- Science
- Biology
- Education
- Mathematics
- Arts and Literature
- Social Sciences
- Law
- Humanities
- Materials Science
- Chemistry
- Psychology
- Earth Sciences
- Environment
- Linguistics
- Philosophy
- Electrical Engineering
- Sports and Recreation
- Design
- Physics
- 14 more »
- « less
-
lightweight deep learning model for welding defect recognition. Weld. World. https://doi.org/10.1007/s40194-024-01759-9 3. J. Franke, F. Heinrich, R.T. Reisch, “Vision based process monitoring in wire arc
-
theoretical and practical state of the art artificial intelligence/machine learning algorithms that are focused on human behavior modeling related to video classification using deep learning networks for end
-
paper, including the previous developments, should be published and our group established as one of the players in the area of deep-learning for computational mechanics. Legislation and Regulations
-
well as experience in omics data analysis, and possesses solid English-language skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX
-
independently and collaboratively Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous Effective communication skills and an interest in contributing to a highly international
-
(pre-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models; integration and analysis
-
efficient deep learning and support to teaching and outreach on sustainable and multimodal AI. Where to apply Website https://www.unimore.it/ Requirements Additional Information Eligibility criteria Eligible
-
doctoral student in the field of chemistry to work on development of deep learning models for estimating protein-ligand binding energies. The specific project is a part of a large-scale collaboration
-
) Knowledge of HIPAA and research data security requirements Experience with deep learning approaches for clinical NLP Equal Opportunity Employer / Disability / Veteran Columbia University is committed
-
good knowledge of Efficient Learning for computer vision Coding Skills: 1. Familiar with any of the major deep learning libraries, including Pytorch We regret to inform that only shortlisted candidates