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Field
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) algorithms in realistic network settings and explore hybrid approaches that combine classical and post-quantum techniques. The project will involve protocol design, system-level evaluation, and performance
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. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience, as well as skilled at estimating and optimizing complexity of algorithms
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the Faculty of Medicine and Health Sciences at NTNU. It was established as a Centre of Excellence in 2002, 2012, and again in 2023. Our Centre of Excellence, the Center for Algorithms in the Cortex (https
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within the Norwegian Center on AI for Decision (aiD), benefiting from broad and divers expertise, and strong industrial connections. The project will have theoretical and algorithmic developments, software
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information sources and to provide the relevant analysis of all the available variables in different scenarios conditions. In order to reach this goal, deep learning-based algorithms will be implemented
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. The project will have theoretical and algorithmic developments, software developments, and industrial case studies. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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collaborators. Tasks include formulating optimisation problems, developing algorithms for optimisation with Bayesian models, and implementing solutions in relevant software. Further tasks include the formulation
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion