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on the development of novel atomic oxygen (ATOX) resistant coatings to increase the durability and reduce drag of satellites in very low Earth orbit (VLEO). The postdoctoral research will focus on developing and
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advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. He/she will support the development of an improved forest RTM that can
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three points: material properties, harvester design and signal conditioning, have to be addressed. This Postdoc position is mainly focused on development of energy harvester based on ceramics. Several
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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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deposition (ALD) is strongly preferred · Experience in coating development for advanced materials, polymers, composites, or barrier applications is considered an asset · Previous experience 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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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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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