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Diversity, Equity and Inclusion St. Jude Children’s Research Hospital has a diverse, global patient population and workforce, built on the principles of diversity, equity and inclusion.
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Other desirable skills include the ability to perform computational biology analyses of next-generation sequencing data and experience with various mouse cancer models. We utilize a range of techniques, including biochemical and molecular biology methods, next-generation sequencing (including single-cell sequencing), and genome editing to study these processes in cell culture, mouse models, and patient-derived models.
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A strong background in statistics, biostatistics, computer science and/or computational biology is required; and specifically, experience with analyzing high-dimensional datasets, such as whole-genome sequencing, multi-omics data, and electronic health records, is preferred.
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Experience working with Next-Generation Sequencing Data. Experience building NGS pipelines in a clinical setting. Computational skills using Python and/or R. Ideal candidates will possess: Experience in cancer genetics, immunology, and/or molecular biology.
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Description Job Responsibilities:We are seeking a highly motivated and experienced individual to help coordinate the computational core within the Machine Biology Group/de la Fuente Lab. As the Computational Core Scientist, the candidate will play a pivotal role in advancing our cutting-edge research at the intersection of computational biology and ground-truth experimentation.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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Demonstrated expertise in molecular biology techniques, including DNA/RNA extraction & purification, NGS library preparation & QC, PCR, qPCR, etc. Generate NGS libraries and perform library QC upstream of sequencing.
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New faculty will join a multidisciplinary, and collaborative research environment to complement strengths in chemical biology, cancer biology, biochemistry, immunology, organic/medicinal chemistry and drug discovery & development within the Center for Experimental Therapeutics and broadly across the OHSU Knight Cancer Institute.
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The Fairbrother Laboratory uses a combination of computational biology and high-throughput genomics techniques to identify functional elements in the genome. Preferred: Specific experience in RNA/DNA purification and analysis, next-generation sequencing, biochemistry, or cellular imaging.
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The AI for Science team has been focusing on tackling challenges in natural sciences, including biology, physics, and materials, with computational tools such as Machine Learning, Computational Chemistry, High-throughput Computation.
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Candidates with a PhD in bioengineering, computer science, physics, mathematics, statistics, cell and molecular biology, biotechnology, or any related field in the life sciences with strong expertise in computational biology and bioinformatics highly preferred.
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Driving high-caliber, interdisciplinary research grounded in computational biology, applying a deep understanding of early biology/target discovery, drug discovery, biomarker discovery and translational investigation as well as an understanding of the computational and data-management infrastructure required to support these programs.
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In this role, the candidate will work collaboratively and cross-functionally with colleagues to develop molecular methods (PCR) and Next-Generation Sequencing (NGS) workflows that support the surveillance, diagnostics, and research efforts of the California Department of Public Health.
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Research, design, and deliver training materials to effectively communicate, promote, and advance computational biology techniques and software usage by NIH researchers. Good understanding of genomics, molecular biology, and technologies such as qPCR and next-generation sequencing.
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PhD. in computational biology, bioinformatics, or other biomedical sciences with a minimum of seven years’ experience in applying bioinformatics approaches to drug discovery/development, preferably in a biopharma setting.
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