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, including EEG. You will design and optimize experimental tasks, collect and analyze behavioral and neural data, and adapt computational models to capture variability between individuals. What you will be
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control of upper-limb prosthetic devices. You will develop machine learning methods that combine neural signals with environmental context to enable seamless object manipulation. The objective is to create
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comprehensive databases combining nationwide Norwegian health and socioeconomic registry data, biobanks and patient-reported data. Using advanced epidemiological methods, causal inference and machine learning
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are searching for a motivated PhD candidate to design practical over-the-air computing algorithms and protocols for future edge AI applications. About the employer The research of this PhD position will be
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models, designing controllers that exploit the system’s distributed dynamics, and validating them experimentally on soft robotic platforms in our lab. These include tentacle-like manipulators and soft arms
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experiments, design and implement advanced detection techniques, analyse data, and carry out numerical trajectory simulations of deceleration and scattering processes. You will have the opportunity to work with
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at the edge. The project explores advanced topics such as TinyML, neuromorphic design, reconfigurable logic, and autonomous fault recovery, with applications ranging from aerospace, energy, and robotics
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partnerships in Luxembourg and Europe that works on responsible and independent research projects · Sustainable by design, empowering our belief that we play an essential role in paving the way to a green
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drug design” is led by Docent Juri Timonen, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug
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exceptional labs occupying more than 5,000 square metres, including innovations in all that we do ·An environment encouraging curiosity, innovation and entrepreneurship in all areas ·Personalized learning