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significant role in learning in AI by enabling cognitive agents to acquire actively knowledge and skills through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and
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Description: This project is in the research field of applied evolutionary ecology, aiming at understanding ecological and evolutionary processes that may be relevant for the development of sustainable plant
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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Description of the offer : The Applied Spintronics Group, University of Gothenburg, Sweden, led by Prof. Johan Åkerman, focuses on magnetodynamic phenomena, spin and orbital torques, nanofabrication
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infrastructure of unique technologies. You will work in the group “Proteomes of Metabolism ” led by Assist. Prof. Florian Rosenberger. We develop and apply cutting-edge mass spectrometry technologies down
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transparent models. The Privacy-aware transparency decisions research group (led by Prof. Vicenç Torra) conducts research in data privacy for data to be used for machine and statistical learning. It is well
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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applications and applications sent by email will not be considered. Application deadline: Oktober 15, 2025 For questions, please contact: Prof. Tünde Fülöp, Subatomic, High Energy and Plasma Physics Email: tunde
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of the results The position is within the research group of Prof. Ingela Lanekoff that strives to develop and establish new innovative method within the research field of analytical chemistry. The research is