9 digital-phd-position PhD positions at University of Southern Denmark in Denmark

PhD Position in Neuromorphic Bioelectronics for Brain-Computer Interfaces: CMOS Design of Analog Front-End and Sensor Interfaces for Wearable

University of Southern Denmark | Denmark | about 1 hour ago

for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive

PhD Position in Power-to-X: Experimental and AI-Driven Optimization of Green Hydrogen and Synthetic Fuel Production PhD Scholarship in Product Assembly and Smart Manufacturing

University of Southern Denmark | Denmark | about 2 months ago

) invites candidates to apply for one or more fully funded 3-year PhD position. The (IDE) Research Unit SDU Innovation and Design Engineering is a young, dynamic, and growing research unit. Research-based

PhD Position in Neuromorphic Bioelectronics for Brain-Computer Interfaces: CMOS Spiking Neural Networks (SNNs) for Neural Signal Processing

University of Southern Denmark | Denmark | about 15 hours ago

? We invite applications for a PhD position, focusing on the design and implementation of Spiking Neural Networks (SNNs) using CMOS technology. Project Overview This PhD position is part of a

PhD Position in Design and Development of Optimized Power Electronic Converter PhD Position in Control of electric machines using WBG semiconductor based power converter PhD position in Cryogenic CMOS design for controlling large-scale quantum devices PhD position in “Use of Technology in Education: Children’s Education in STEM and Technology in the Danish and German Primary and Secondary Schools

University of Southern Denmark | Denmark | 3 months ago

to the position. Completed TEK PhD application form for 5+3 applicants. Find the form at the Faculty website . Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website

PhD Positions in Demonstration-Initialized Reinforcement Learning for Robotic Manipulation