Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Engineering
- Biology
- Medical Sciences
- Science
- Economics
- Materials Science
- Earth Sciences
- Chemistry
- Mathematics
- Business
- Linguistics
- Electrical Engineering
- Environment
- Arts and Literature
- Education
- Law
- Psychology
- Humanities
- Philosophy
- Physics
- Social Sciences
- Sports and Recreation
- 13 more »
- « less
-
NIST only participates in the February and August reviews. The fire modeling community is actively working to develop the tools needed to quantitatively predict material and product flammability
-
14 Mar 2026 Job Information Organisation/Company Scuola IMT Alti Studi Lucca Research Field Computer science » Modelling tools Engineering » Control engineering Physics » Applied physics Engineering
-
) approaches. Design predictive maintenance algorithms using machine learning, statistical learning, and digital twin-based models to anticipate failures and optimise maintenance interventions. Integrate AI
-
. Furthermore, a novel predictive algorithm of School-age neuropsychological outcome will be developed combining radiomic model of brain development, with qualitative neonatal MRI findings. Achievement
-
design strategies, while producing structured spatio-temporal datasets that will serve as input for realising predictive models. Objective 3 — Realize predictive tools for scenario-based assessment
-
Are you a researcher driven to understand and predict the fundamental mechanisms limiting lithium-ion battery performance? We are recruiting a Research Associate in Lithium-Ion Battery Modelling
-
, manufacturing) by creating applications for critical systems, adaptive and autonomous systems, advanced perception, diagnostics, quality control, and prediction systems. Further research areas include precision
-
predictive models for failure control. Validation & Experimental Collaboration: Compare simulations with experiments, collaborate on proof-of-concept testing, and refine models based on results. Where to apply
-
approaches capable of guiding experiments, interpreting results in real time, generating predictive models of materials synthesis processes, and refining experimental strategies under a Human-In-The-Loop
-
, and generate high-quality datasets for predictive microbial modelling and risk assessment. Responsibilities include contributing to the design and execution of food challenge studies, integrating