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Field
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will join an international and multidisciplinary team and will work in the project which aims to develop an innovative, modular, and partially bioresorbable wound filler for Negative Pressure Wound
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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest
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new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
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on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order models, designing controllers that exploit
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-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
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nature. The PhD candidate will focus on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order
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”. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions and Regulations for the degrees philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work
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for the degrees philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred
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scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest ML tools and frameworks
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such as textiles. 2. Proven ability to develop and implement advanced motion-planning algorithms and real-time control schemes, ideally demonstrated through digital-twin simulations and hardware-in-the-loop