Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Germany
- France
- Portugal
- United Kingdom
- Sweden
- Spain
- Singapore
- Norway
- Italy
- Belgium
- Netherlands
- Denmark
- United Arab Emirates
- Poland
- Australia
- Luxembourg
- Romania
- China
- Canada
- Hong Kong
- Ireland
- Estonia
- Japan
- Finland
- Austria
- Worldwide
- Czech
- Greece
- Morocco
- Switzerland
- Andorra
- Brazil
- Bulgaria
- Croatia
- Cyprus
- India
- Malta
- Saudi Arabia
- Slovakia
- Armenia
- Europe
- Israel
- Mexico
- New Zealand
- 35 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Mathematics
- Economics
- Science
- Electrical Engineering
- Materials Science
- Chemistry
- Earth Sciences
- Linguistics
- Business
- Humanities
- Physics
- Psychology
- Social Sciences
- Arts and Literature
- Environment
- Philosophy
- Education
- Design
- Law
- Sports and Recreation
- 14 more »
- « less
-
are: i) to develop a new selected CI algorithm allowing reaching chemically-accurate results for large compounds; ii) to extend the currently-available database to properties relevant for both core
-
programme Reference Number AE2026-0039 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0039
-
, domain adaptation, multimodal AI) to analyze plant and environmental data. Support the integration of AI algorithms with robotic and sensing systems for real-world deployment. Assist in experimental design
-
algorithms into electron impact ion sources as well as tackle changes over time in ISOL systems, to ensure an optimal tuning at any point in time during operation. Where to apply Website https://www.sckcen.be
-
: Bioinformatics, biostatistics, and health data science General computer science: programming, algorithms, and theory Software engineering The candidates must hold a doctoral degree in any of the areas listed above
-
algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research group's efforts in modeling combustion-generated aerosols. These modeling framework will be used to understand
-
The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
-
state-of-art research training to post-doctoral fellows, Ph.D. and Master students in the field. For more information about the center, please visit http://csiss.gmu.edu/. George Mason University College
-
architectures such as convolutional neural networks, transformers, and diffusion models. Proven experience building AI solutions using classical ML algorithms such as decision trees, gradient boosting machines
-
or computer science, or a related discipline (or equivalent experience). A doctoral level qualification involving methodologies deploying advanced statistical, mathematical or algorithmic techniques, or directly