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to biological data. PREFERRED QUALIFICATIONS: PhD in Bioinformatics, Computational Biology, Computer Science, or a related field Experience applying deep learning or foundation-model approaches to sequence-based
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research ranging from lattice light-sheet microscopy to CryoEM, genomics, and informatics. You will work with PhD-level bioinformatics scientists and researchers who have single-cell RNA-seq and spatial
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Qualifications PhD degree in bioinformatics or a related inter-disciplinary field High level of motivation for research, attention to detail, scientific creativity, and writing skills Languages skills: fluent in
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bioinformatician position at Lund University! National Bioinformatics Infrastructure Sweden (NBIS; https://nbis.se) is a large national infrastructure in rapid development providing support, tools and training
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-edge research ranging from lattice light-sheet microscopy to CryoEM, genomics, and informatics. You will work with PhD-level bioinformatics scientists and researchers who have single-cell RNA-seq and
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analysis Your profile: Requirements: PhD in Zoology, Evolutionary Biology, or a related field with a focus on biodiversity genomic methods, bioinformatics, phylogenomics, and marine invertebrate systematics
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metatranscriptomics. We are looking for a dynamic and motivated PhD student to conduct innovative scientific research in the field of microbial ecology and applied bioinformatics. The use of various -omics tools means
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, to perform data analysis derived from diverse scientific topics in collaboration with PhD students and postdocs, to train students and postdocs in basic data analysis pipeline implementation and bioinformatics
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. Background and objectives The Tangney lab is currently seeking PhD students with an interest in wetlab and /or drylab (bioinformatics, sequence data analytics, protein design). This project is part of
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use of computational bioinformatics and biostatistics techniques to investigate the biological correlates of cancer cachexia by analysing existing genomic and transcriptomic sequencing data from multi