Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Engineering
- Biology
- Medical Sciences
- Science
- Economics
- Materials Science
- Earth Sciences
- Mathematics
- Business
- Chemistry
- Electrical Engineering
- Linguistics
- Arts and Literature
- Environment
- Law
- Physics
- Education
- Humanities
- Philosophy
- Psychology
- Social Sciences
- Sports and Recreation
- 13 more »
- « less
-
challenges related to data reliability in monitoring networks, which can affect simulation models or related control systems. Collaboration with multidisciplinary teams will be essential, as the research
-
Charité–Universitätsmedizin Berlin (Dr. Rosanna Sammons); for further information, see https://www.sfb1315.de/ - development of network models of the CA3 region of the hippocampus - investigation
-
prediction models, and visualizing immense volumes of various types of data, generated by agri-robots and IoT devices. The most popular classes of autonomous agricultural devices include: weeding robots
-
Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 2 months ago
control theory (e.g., model predictive control, fuzzy control, etc.) # Excellent teamwork and communication skills in an interdisciplinary and international research environment # Motivation and self
-
models ignore this exposome. In BEE, we will build explainable, physics-guided, GeoAI-driven models that: Predict acute and chronic NCD risks at the population scale Identify vulnerable neighbourhoods and
-
injury risk analysis, predictive analytics, and recruitment and talent identification models; Works with individual players and helps them develop on the field through video analysis; Participates in
-
digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In
-
Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
-
project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
-
polygenic risk scores, rare variant burden scores, and integrative prediction models. Evaluate model performance and clinical utility. Identify therapeutic targets and causal risk factors for cardiovascular