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equivalent)) Knowledge of simulation platforms like MATLAB Simulink/PLECS. Coding and hardware skills are desirable. Strong analytical/mathematical skills. Passion for research and willingness to learn. Good
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an academic paper, discussing requirements with hardware engineers, or presenting at a conference. Self-driven: While you will be fully supported by your supervisors and the research group, you take ownership
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signal processing methods and a modelling environment, aided by unique hardware-in-the loop, to assess the detection and estimation algorithm performance and determine optimal multistatic configurations
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of Computer Science We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual
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systems for measurement processes, or innovative hardware and software for quantum computers and quantum sensors: we develop tomorrow’s technology in-house for a sustainable and secure society. Become part
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
well as experience in computer vision and machine learning. Your tasks will be to: Develop and enhance capture systems, which include creating the hardware system and study design. Data collection using the developed
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-Royce, Thales, and UKRI—offering global relevance in low-power AI hardware, embedded intelligence, and adaptive electronics. The rapid advancement of Artificial Intelligence (AI) has necessitated
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experience with robots and/or other hardware is desirable but not required. We expect applicants to hold a Master’s degree in a relevant field such as human-computer interaction, computer science, software
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(e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects of machine learning such as
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 3 months ago
(improving scalability, vectorization, implementation of hybrid parallelization using MPI+OpenMP), - application porting to modern hardware architectures, · compilation of parallel applications and libraries