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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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related disciplines Quantitative imaging, data analysis, or computer vision Numerical modeling of biological systems or continuum mechanics Machine learning/AI, particularly explainable AI (XAI) Hands
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postdoctoral researchers, supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because
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learning, e.g. using JAX, based on numerical models such as Higher Order Spectral method, mcsimpy, etc. Collect real metocean data from relevant online databases, datastreams such as from R/V Gunnerus, and
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-resolved prediction of wave elevation and wave loads in continuous time. Look into fusing the models into a foundational model. Setting up a synthetic training gym as a platform for AI model learning, e.g
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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syndrome. Targeted projects currently include the following: Use AI/machine learning approaches to develop a means to quantify and classify tic movements and vocalisations in Tourette syndrome/tic disorder
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dynamics to neuroaesthetics Modelling Oscillations in Human Immune & Neuroimmune Cells Multi-level modelling of neuromodulation and lesioning Multimodal Machine Learning for Psychological Profiling
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students, and about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department