Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Education
- Business
- Engineering
- Computer Science
- Biology
- Medical Sciences
- Electrical Engineering
- Physics
- Psychology
- Statistics
- Chemistry
- Materials Science
- Earth Sciences
- Social Sciences
- Environment
- Mathematics
- Humanities
- Law
- Sports and Recreation
- Arts and Literature
- Design
- Economics
- Philosophy
- 13 more »
- « less
-
-grain 3D integration, advanced packaging, backside power delivery networks, and chiplet-based architectures require new methodologies to model and optimize system behaviour beyond the traditional
-
implementation or comparable tools. Experience with one or more relevant methods, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization
-
Industrial Applications.” Available: https://www.iiconsortium.org/pdf/IIC_Digital_Twins_Industrial_Apps_White_Paper_2020-02-18.pdf [3] A. Ebrahimi “Challenges of developing a digital twin model of
-
research and scientific publications Strong background in control, robotics and machine learning, and experience in areas like model predictive control, adaptive control, reinforcement learning, robot
-
research and scientific publications Strong background in control, robotics and machine learning, and experience in areas like model predictive control, adaptive control, reinforcement learning, robot
-
Research Center for Molecular Medicine (CeMM), ÖAW | Graz,12.Bez.:Andritz, Steiermark | Austria | 27 days ago
measurements inform predictive models; models generate hypotheses and designs; interventions test and reshape metabolic systems. A major long-term ambition is the construction of a quantitative model —a
-
written and spoken English. Experience with some of the areas of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi
-
Job Description We are seeking a highly motivated Research Assistant in the area of damage modeling of large-scale composite structures. Our research focuses on developing predictive numerical tools
-
-effective steam production.The PhD position in The SySi Team will focus on the integrated steam system design and control in a multi-energy vector context, using physics-based non-linear Model Predictive
-
model predictive control, machine learning, or reinforcement learning. Experience with IoT, edge computing, and cloud integration. Proven ability to contribute to research funding proposals