Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
an algorithm to be implemented in Python.
-
their reliability and resource efficiency during production and operation. The »KI-unterstütze Simulation« team combines physically based simulation approaches with efficient and advanced mathematical algorithms and
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
-
. Because of the specific structure of the inference problems occurring in metabolic models, direct application of these MCMC algorithms is, however, not possible. In this project, you will bring MCMC methods
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
-
and their processing on the FPGA of a frame grabber card You will program the PC software for configuring and controlling the algorithms on the FPGA Your tasks will include designing the transfer
-
. Your main Responsibilities Perform original and excellence-driven research: Develop and analyze dynamic models and guidance and control algorithms Conceptualize and develop sample scenarios, roadmaps and
-
research: Develop and analyse mathematical models for the dynamics of evolving self-assembled systems (orbital, attitude, multi-body, RV-docking), as well as for guidance and control algorithms Conceptualize
-
operating conditions Design and implement optimization algorithms to improve the performance of the engine, battery, fuel cell, transmission, and hydraulic systems, considering constraints such as component
-
. Therefore, we employ a broad range of artificial intelligence algorithms that enrich process data with sophisticated domain knowledge and semi-supervised approaches to incorporate unlabeled data. We