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be addressed. This Postdoc position is mainly focused on development of energy harvester based on ceramics. Several challenges will be addressed to achieve targeted values of power from tires
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actively shape interdisciplinary theory on sustainable transformations and well-being. The successful candidate will join the Institute for Lifespan Development, Family and Culture within the Department
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deep learning. You will support the development of an improved forest RTM that can exploit LiDAR full-waveform data along with hyperspectral signatures. You will plan and carry out field campaigns in
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and related research and development by: Co-developing and co-teaching GCE modules for primary school teachers and educators Conducting education research related to the development and implementation
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Poltavskyi, a leading expert in MLFFs, and within the Theoretical Chemical Physics group led by Prof. Alexandre Tkatchenko, one of the world’s leading groups in machine-learning force-field development
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on the development of technology for lunar and Martian regolith handling and beneficiation. · Develop and apply modelling and simulation approaches to particle separation systems. · Optimize the design
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partners as well as national and international academic initiatives. These projects span the full research and development lifecycle, requiring large-scale experimentation, real-time system implementation
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Planning focuses on spatial development processes on local, regional and international scales. Faculty endeavor to understanding transformation processes and in developing recommendations for sustainable
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translational and scalability considerations. Responsabilities: Lead the development of hybrid foundation model–graph neural network architectures for gene perturbation prediction, including the design and
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to collaborative research activities within the team. • Supporting or leading the preparation and development of new project proposals. • Supporting knowledge transfer and demonstration of developed solutions in