Sort by
Refine Your Search
-
Listed
-
Country
- United States
- United Kingdom
- France
- Sweden
- Italy
- Germany
- Spain
- Australia
- Belgium
- Netherlands
- Portugal
- Canada
- Czech
- Luxembourg
- Singapore
- Finland
- Poland
- China
- Denmark
- Ireland
- Andorra
- Austria
- Estonia
- Hong Kong
- Hungary
- Japan
- Macau
- Malta
- Switzerland
- United Arab Emirates
- Barbados
- Morocco
- Norway
- Saudi Arabia
- 24 more »
- « less
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Biology
- Science
- Business
- Mathematics
- Materials Science
- Environment
- Earth Sciences
- Chemistry
- Psychology
- Humanities
- Law
- Linguistics
- Sports and Recreation
- Arts and Literature
- Education
- Physics
- Social Sciences
- Electrical Engineering
- 12 more »
- « less
-
. Please review the call carefully before applying. 1. General Context Time-Sensitive Networking (TSN) extends the Ethernet standard to support deterministic communication, guaranteeing predictable and
-
NOBM using prognostic fluxes predicted by the GISS climate model in order to characterize the dust pathways, the timing and magnitude of dust-iron deposition events, the regional and temporal variations
-
for critical systems, adaptive and autonomous systems, advanced perception, diagnostics, quality control, and prediction systems. Further research areas include precision farming, robotics, metrology, cultural
-
, skills, and experience in translating complex business needs into technical solutions using advanced analytics, including predictive modeling and statistical analysis, to drive institutional decision
-
—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from
-
feed artificial intelligence models to predict fermentation performance and market impact. Where to apply Website https://www.univr.it Requirements Additional Information Eligibility criteria
-
physics-informed machine-learning models for binding affinity predictions in rational small-molecule drug design. The models will allow prioritisation of candidates from hit discovery through to lead
-
atmospheric physicochemical processes for the development of better predictive meteorological models (intensities and locations) and the distribution of pollutant contamination in the air, thus helping to make
-
protein structural insight with hands‑on ML development: adapting and applying state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational
-
Intelligence Unit looking for talented and motivated candidates to work on applying AI techniques to model, predict and optimize energy systems. Join us at the heart of a mission that truly matters: transforming