/wp-content/uploads/2019/11/silvaco-logo.png00Gigi Boss/wp-content/uploads/2019/11/silvaco-logo.pngGigi Boss2022-02-28 12:49:322022-05-24 08:46:32Silvaco Announces that Teledyne e2v Expands Adoption of its Victory TCAD Solution to Further Accelerate Development of CMOS Image Sensors
/wp-content/uploads/2019/11/silvaco-logo.png00Gigi Boss/wp-content/uploads/2019/11/silvaco-logo.pngGigi Boss2022-02-24 11:00:212022-05-24 11:13:43Silvaco’s Dr. Firas Mohamed Elected to Co-chair of Si2 Artificial Intelligence/Machine Learning Special Interest Group
/wp-content/uploads/2019/11/silvaco-logo.png00Gigi Boss/wp-content/uploads/2019/11/silvaco-logo.pngGigi Boss2021-09-02 06:00:242022-05-24 08:48:48iDEAL Semiconductor Adopts Silvaco Victory TCAD Solution for the Development of Next-Gen High Efficiency Power Devices
/wp-content/uploads/2019/11/silvaco-logo.png00Erick Castellon/wp-content/uploads/2019/11/silvaco-logo.pngErick Castellon2020-11-24 00:00:472020-11-24 00:00:47IRIS Switzerland Adopts Silvaco TCAD Software for the Development of Photodiodes for Autonomous Driving Applications
/wp-content/uploads/2019/11/silvaco-logo.png00Erick Castellon/wp-content/uploads/2019/11/silvaco-logo.pngErick Castellon2020-08-25 17:00:412020-08-25 17:00:41SemiQ Switches to Silvaco TCAD for Design of Power Devices
/wp-content/uploads/2019/11/silvaco-logo.png00Erick Castellon/wp-content/uploads/2019/11/silvaco-logo.pngErick Castellon2020-04-02 00:00:132020-04-02 00:00:13Trixell Adopts Silvaco TCAD-based Parasitic Extraction Solution for Development of New Display Technology
Feb. 5, 2020
On the 4 th and 5th of February 2020, in Montpellier (France), at the premises of LIRMM, CNRS the Kick-off meeting of NeurONN took place. All the Partners of the NeurONN Consortium met and set the ground for the activities along the three-year duration of the EU Project
/wp-content/uploads/2019/11/silvaco-logo.png00Graham Bell/wp-content/uploads/2019/11/silvaco-logo.pngGraham Bell2020-02-05 00:33:582020-02-05 00:33:58Two-dimensional oscillatory neural networks for energy efficient neuromorphic computing
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