Sort by
Refine Your Search
-
is embedded in the TechMed and DSI Institutes. [https://www.ram.eemcs.utwente.nl/] About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses
-
is embedded in the TechMed and DSI Institutes. [https://www.ram.eemcs.utwente.nl/] About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses
-
developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
-
within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
-
environment that encourages professional growth, mentoring, and a healthy work–life balance. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses
-
partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
-
Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented Postdoc/researcher (m/f/x). Job description We are looking for a motivated postdoctoral
-
). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
-
) to develop computational models for electric breakdown of gases Job description Electric gas discharges occur in nature, most prominently in air in the form of lightning and its less visible precursors
-
applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning