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Field
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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biology, bioinformatics, bioimaging, and genomics, with an emphasis on the bioinformatics analysis of small RNA transcriptomes, and RNA molecular quantification. Working under the direction of the Principal
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setting. We’re seeking a senior scientist with: A strong background in human genetics and statistics Proven expertise in analysing genomic and transcriptomic datasets A drive to tackle complex biological
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development and human diseases, such as neurological disorder, immunology, and cancer. Utilize biochemistry, molecular biology, CRISPR-based genomic screen, single-cell transcriptomics, and genetically modified
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, transcriptomic, proteomic or imaging datasets would be advantageous. Application Please send the following materials to [email protected]: A curriculum vitae, including a publication list. A brief description of
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histology datasets. Applying graph neural networks, transformer models and generative AI approaches to study clone-microenvironment interactions. Integrating spatial transcriptomics, single-cell sequencing
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 11 hours ago
, transcriptome, and proteome (so-called "omics"). Large-scale proteomics data has the potential to identify clinically meaningful biomarkers for predicting disease progression, monitoring treatment efficacy, and
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, transcriptomic, proteomic, and circulating biomarker data. The lab provides access to state-of-the-art computational infrastructure, including high-performance computing (HPC) environments, GPU-enabled systems
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PTLD patient and control patient blood and are performing single cell spatial transcriptomics to analyse the immune microenvironment of PTLD tumours. The appointed candidate will create and contribute
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myeloid leukemia (AML), and natural killer/T-cell lymphoma (NKTL). The successful candidate will contribute to projects utilizing genomics, transcriptomics, proteomics, and functional studies to identify