Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Norway
- Sweden
- France
- Belgium
- Denmark
- Netherlands
- Singapore
- Portugal
- Spain
- Australia
- Hong Kong
- China
- Austria
- United Arab Emirates
- Poland
- Switzerland
- Canada
- Luxembourg
- Italy
- Ireland
- Czech
- Estonia
- Finland
- Latvia
- Cyprus
- India
- South Africa
- Andorra
- Morocco
- Romania
- Lithuania
- New Zealand
- Brazil
- Bulgaria
- Croatia
- Slovenia
- Worldwide
- Armenia
- Israel
- Japan
- Saudi Arabia
- Barbados
- Europe
- Greece
- Iceland
- Malta
- Qatar
- Slovakia
- Taiwan
- Vietnam
- 43 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Biology
- Economics
- Science
- Mathematics
- Business
- Chemistry
- Arts and Literature
- Social Sciences
- Materials Science
- Education
- Humanities
- Psychology
- Linguistics
- Electrical Engineering
- Environment
- Earth Sciences
- Law
- Physics
- Design
- Sports and Recreation
- Philosophy
- Statistics
- 15 more »
- « less
-
disciplines such as neuroscience/cognitive science, AI and machine learning, robotics, engineering, computer vision, and signal processing. Details of this year’s workshop are at https://sites.google.com/view
-
FAIR principles, combined with skills in statistical analysis, machine learning and/or data science. Experience with programming languages such as R, Python, or similar will be considered an advantage
-
the following areas desirable but not essential: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show initiative, creativity, and to work independently Excellent
-
with experience in ligand discovery. Our research group is focused on developing state-of-the-art computational methods for ligand/drug discovery, using machine learning, high-performance/cloud computing
-
, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
-
yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
-
Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology
-
an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
. Picchini. Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings. Transactions on Machine Learning Research, 2024 Kugler, F. Forbes, and S. Douté. Fast
-
. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness