23 molecular-modeling-or-molecular-dynamic-simulation positions at Linköping University
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generative models, geometric machine learning, dynamical systems, and/or multi-modal learning. From the materials science perspective, our primary focus will be on ultra-thin, so-called, 2-dimensional
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models all the way to the materials discovery lab. From the machine learning perspective, your research will be in the area of generative models, geometric machine learning, dynamical systems, and/or multi
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level in electrical engineering, electromagnetic engineering, wireless engineering, engineering physics, applied physics, a closely related field. Good command of electromagnetic simulation tools such as
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, where models learn to restore images using only the noisy data itself — without requiring clean references. Existing approaches often rely on convolutional neural networks (CNNs), which identify local
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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embodied AI agents can dynamically adapt to group behaviors and learning needs The project will combine observational studies, interaction design, and experimental evaluations to develop embodied AI-driven
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approximately 30 places. The department strives for an approach that encourages and promotes the use of theories and models drawn not only from traditional social sciences, but also from, for example
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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: Verifiable training and trustworthy AI pipelines. Tools for robust data and model provenance in adversarial environments. Methods for protecting training data and end users, including secure data removal and