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the Norwegian Pharmacy Foundation. The main focus of ’the research group’s work is the optimization of the medication use of the individual, patient living with multiple long-term conditions. This also applies
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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The position belongs to the research group for clinical pharmacy , and is funded by the Norwegian Pharmacy Foundation. The main focus of ’the research group’s work is the optimization of the medication use
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and control. This can involve optimizing robots through techniques from Evolutionary Robotics in a simulator, and then deploying robots for further training and subsequent testing in lab- or real-world
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-design of morphology and control. This can involve optimizing robots through techniques from Evolutionary Robotics in a simulator and then deploying robots for further training and subsequent testing in
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. The main focus of ’the research group’s work is the optimization of the medication use of the individual, patient living with multiple long-term conditions. This also applies to the planned project
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therapy. The project will involve both physics-based forward modeling of protein structures and reinforcement learning methods for optimizing the structures. The outcome from the models will be tested in
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agencies, and leading global institutions. The PhD Research Fellow will focus on enabling robust, intelligent robots through co-design of morphology and control. This can involve optimizing robots through
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structures, the development of effective architecture for machine learning classification of the structures, and reinforcement learning methods for optimizing the structures for particular applications
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that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing