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Work in Stockholm, in close proximity to nature A research environment with a strong base in use of super-resolution microscopy for biomolecular applications State-of-the-art laboratories in cell biology
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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Description of the Workplace You will be based at the Faculty of Medicine in Lund. The Unit for Diabetes and Brain Function is located at the Biomedical Centre (BMC) at Lund University and is led by
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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circularity in complex aerospace systems. Via Model Based Systems Engineering (MBSE) we think that it would be possible to successfully predict the effects of proposed design changes on circularity and
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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part of the Swedish Research Council (Vetenskapsrådet)-funded project “PolyKinetics” and is based in the Laboratory of Organic Electronics at Linköping University, Sweden. As part of this project, you
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bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral
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abundant side streams into high-value bio-based materials, contributing directly to the circular bioeconomy. You’ll work with cutting-edge bioprocessing tools, collaborate with leading European partners, and
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various bio-based resources, a critical step in improving their stability for diverse applications. Therefore, besides the scientific tasks, the position also includes responsibility for research