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will handle and analyse large amounts of data from brain imaging (MRI and PET), cognitive tests, blood-based biomarkers; and perform statistical analyses. The appointment aims at a PhD degree and the
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measurements to the results of existing techniques using backscatter to quantify forest attributes through synthetic aperture radar imaging. The overall project, spanning multiple institutions, aims to produce a
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) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and
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-cell imaging and analysis will be used to investigate cell and cluster morphology. The scientific interests and background of the PhD student will be a major factor in the design of the project. A person
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of molecular pharmacology, biochemical, and cellular assays to discover new small molecule and antibody-based prototype drugs. SciLifeLab DDD maintains a semi-industrial environment within the universities where
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of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received
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-throughput sequencing of genomes and biomes, continuous recording of video and audio in the wild, high-throughput imaging of biological specimens, and large-scale remote monitoring of organisms or habitats
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-dimensional statistics, and optimization. Documented experience in working with biological data, especially genomics, or other types of high-dimensional data such as imaging. Excellent programming skills in
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in Python and MATLAB, particularly in machine learning, data analysis, and image processing. Experience working in Linux environments. Ability to collaborate in interdisciplinary teams and work with
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data streams offered by techniques such as high-throughput sequencing of genomes and biomes, continuous recording of video and audio in the wild, high-throughput imaging of biological specimens, and