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and international network focusing on sustainable agriculture. We conduct research for sustainable agriculture, forest production and biological conservation. Our basic research on populations
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, the Knowledge Foundation (KK-stiftelsen) and industry partners have decided to support Mission 0 House with an additional program, with a budget of nearly 100 million SEK over a five-year period, starting in Q1
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aims to address scientific and sectoral gaps in biological imaging from molecular, cellular, and tissue levels to organ and organism levels of organisation. The programme is coordinated by LINXS, Lund
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technology C3NiT and within a European network within the WBG Pilot Line, but also with experienced researchers within materials growth and materials characterization, at the departments of solid state physics
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to actively participate in the department's environment and networking both internally and externally, as well as develop new project ideas and seek project funding. A certain amount of teaching and supervision
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network of national and international collaborators. Project overview The aim of this two-year project is to validate and further develop advanced numerical models (originally developed at Chalmers
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independently. The workplace The Division of Automatic Control is successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our
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at least 1 million DNA barcodes. The project involves collaboration with a computer vision lab at Linköping University, focused on developing AI-assisted techniques for picking out specimens for genome