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guidelines, including animal monitoring, metabolic assessments, tissue harvesting and biological sample collection and processing Perform and support metabolomic and transcriptomic sequencing analyses
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precision. Second, we must understand what to write - determining which DNA sequences will generate biological systems that perform the desired functions. Addressing these challenges will allow us to harness
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augmentation. Experience applying deep learning methods to biological sequence or other omics data. Demonstrated rigor in model evaluation and experimental design, including selection of appropriate baselines
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Cellular and Molecular Therapeutics Branch, NHLBI, NIH | Bethesda, Maryland | United States | 2 months ago
biology techniques, lentiviral vector technologies, animal models of hematopoiesis, bioinformatics or next-generation sequencing (NGS) analysis. The ideal candidates will be highly motivated, intellectually
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supporting documentation, proven experience in all of the following areas: natural language processing and machine translation (sequence-to-sequence modelling, NMT, glosses); deep learning, Transformers, and
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the at least one of the following high-dimensional data-types: GWAS, RNA-sequencing, proteomic profiling, behavioural, etc. For this project, the ability to work with video, text, language modalities is
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for this position will join a team of computational biologists to work on multi-omic sequencing datasets (DNA, RNA, epigenetic, spatial transcriptomics and spatial proteomics) in the context of pre-clinical and
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datasets, including RNA-seq, ATAC-seq, ChIP-seq, and single-cell or single-nucleus sequencing data. · Present research findings at laboratory meetings, scientific conferences, and national
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to the creation of knowledge by developing a platform technology for the rapid generation of reagents that recognise diverse nucleic acid sequences and structures with high affinity and selectivity using mirror
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Qualifications* Prior experience with mammalian tissue culture, DNA/RNA molecular assays, protein biology, high-throughput genetic screens, and -omics datasets is desired Prior experience with sequencing data