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modelling framework multiple ML tasks as mentioned above, to ease the development burden from users. It will research unified and modular modelling strategies, capable of optimally fusing and aligning diverse
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed
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at diagnosis and relapse, and compare them to healthy hematopoietic specimens using nanopore-based direct tRNA sequencing. Complementary transcriptomic, proteomic, and metabolomic profiling will be performed
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are learning more and more how it relates to human health and disease. The new generation of deep metagenomic sequencing, consists in simultaneous sequencing of multiple microbial genomes at once and has
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project description: Inkjet printing allows multiple materials to be 3D-printed simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage
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MSc/PhD Position at the Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Canada
research project focused on exploring the immunometabolic pathways of macrophages and microglia in multiple sclerosis (MS). The Kaushik Lab is committed to fostering an inclusive and equitable research
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actively contribute to this strategic initiative by researching and developing scalable, practical frameworks for implementing Trustworthy AI principles in diverse projects and across multiple technology
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throughout the horse breeding season (March–August). Your research will bridge basic biology and translational embryology. Using live imaging and single-cell sequencing approaches, you will investigate how
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“Quantitative predictions of protein – DNA interactions from high-throughput biophysical binding data”. Sequence specific binding and recognition between transcription factors and DNA control gene expression at
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project TARGET-AI will bring together expertise from multiple research groups to advance the state-of-the-art in combining the most advanced techniques from deep learning/AI with rigorous statistical