Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- Sweden
- Germany
- Norway
- France
- Denmark
- Spain
- Australia
- Belgium
- Austria
- United Arab Emirates
- China
- Luxembourg
- Switzerland
- Portugal
- Singapore
- Finland
- Canada
- Poland
- Hong Kong
- Italy
- Estonia
- Morocco
- Czech
- Vietnam
- Cyprus
- Brazil
- Greece
- Saudi Arabia
- Latvia
- Malaysia
- New Zealand
- Slovenia
- Taiwan
- Worldwide
- 27 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Biology
- Science
- Economics
- Mathematics
- Psychology
- Earth Sciences
- Environment
- Materials Science
- Education
- Humanities
- Electrical Engineering
- Linguistics
- Business
- Social Sciences
- Chemistry
- Arts and Literature
- Physics
- Law
- Sports and Recreation
- 12 more »
- « less
-
developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
-
. The Department of Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Surface Structures The Data-driven Atomistic Simulation (DAS) group, led by
-
climate will warm and recover in a net-zero future. As part of this project, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques
-
working with large deployed and productionised machine learning pipelines. PRIO offers Contract: 1.5 years, full-time temporary employment, with a salary based on qualifications and experience. Location
-
the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target
-
for GIS, cartographic maps, geodata infrastructures and geo-analytical workflows; some experience with AI and machine learning methods to label texts (NLP) or data sources; strong programming skills (e.g
-
methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and academia. The candidate
-
Productivity Index (RPI) using observed versus potential productivity modelled with machine learning (https://doi.org/10.1016/j.ecolind.2025.113208 ), this applied geospatial ecology project will study how
-
of greenhouse gases including CO2 and CH4. The PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric
-
Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a