Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Engineering
- Biology
- Medical Sciences
- Science
- Economics
- Materials Science
- Earth Sciences
- Business
- Mathematics
- Chemistry
- Electrical Engineering
- Linguistics
- Environment
- Arts and Literature
- Education
- Law
- Physics
- Philosophy
- Psychology
- Social Sciences
- Sports and Recreation
- 12 more »
- « less
-
Familiarity with cleaning and managing large datasets. Strong writing skills. Preferred Qualifications Statistical skills applying artificial intelligence and data science for societal benefit in predictive
-
Predictive Model” project financed from the funds of Priority 2 of the European Funds for a Modern Economy Program 2021–2027 (FENG) Action 2.2 First Team, with the Intermediate Institution being the Foundation
-
IF or CORE A*/A conference paper. Robust machine control assumes modeling of robot-environment interactions. An example may include an outdoor autonomous ground robot that needs to be aware of its
-
) to Volumetric Arc Therapy (VMAT), Stereotactic Radiosurgery (SRS), and ultra-high dose-rate (UHDR-FLASH) therapy, the need for real-time control and verification becomes critical. This PhD will further develop
-
types will change under different climate change scenarios based climate projections. This framework will be ultimately included in a flood prediction model, which will be developed within the VIDI
-
Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Palaiseau, le de France | France | about 2 months ago
appelé Cloud-Resolving Model (CRM). Il s'agit d'un modèle atmosphérique non hydrostatique simulant un domaine local relativement petit (quelques centaines de kilomètres, comparé au rayon de Jupiter de 70
-
execution models towards designing the next-generation unified cloud stack. CloudNG has a strong emphasis on performance and performance predictability, sustainability, seamless accelerator integration, and
-
-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
-
, project and program evaluation, and report writing. Data science and Geospatial Analysis skills, including coding (e.g., Python, R), inferential statistics (e.g., MATLAB, STATA), predictive modeling, GIS
-
efficiency and reliability. Strong background in data analytics, leveraging insights to drive operational improvements and predictive maintenance. Experience in control strategies and automation, ensuring