Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Sweden
- France
- Norway
- Portugal
- Singapore
- Spain
- Belgium
- Netherlands
- Denmark
- China
- United Arab Emirates
- Italy
- Australia
- Canada
- Luxembourg
- Hong Kong
- Switzerland
- Austria
- Finland
- Czech
- Ireland
- Poland
- Estonia
- Japan
- Morocco
- Brazil
- Cyprus
- India
- Latvia
- Romania
- Saudi Arabia
- Lithuania
- South Africa
- Andorra
- Bulgaria
- Greece
- Taiwan
- Israel
- Slovenia
- Armenia
- Barbados
- Europe
- Iceland
- Malta
- Mexico
- New Zealand
- Slovakia
- Vietnam
- 41 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Arts and Literature
- Chemistry
- Social Sciences
- Humanities
- Linguistics
- Earth Sciences
- Environment
- Sports and Recreation
- Law
- Electrical Engineering
- Physics
- Design
- Philosophy
- 14 more »
- « less
-
, TensorFlow, HuggingFace). Model Development and Delivery Support Perform data cleaning, exploratory data analysis (EDA), and feature engineering. Train, evaluate, and compare machine learning models under
-
for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
-
research, machine learning or artificial intelligence (e.g., large language models, EHR foundation models), causal inference (e.g., target trial emulation), and child health research. The research program
-
for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
-
of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) development of novel machine learning models and adaptation of existing approaches for scientific applications
-
network structures. Methods from graph theory, machine learning, and artificial intelligence will be employed to model complex relational structures and identify patterns in high-dimensional data. The work
-
projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
-
with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
-
based on machine learning tools for energy problems related to prediction. The application domains include both industry and climate changes. The first two months will be devoted to the study of
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning