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reusable bioinformatics analysis pipelines for processing RNA -seq, single-cell RNA -seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing
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computational and bioinformatics research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and manuscripts, participate in teaching and
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maintaining scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at
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reusable bioinformatics analysis pipelines for processing RNA -seq, single-cell RNA -seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when
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research, development, and analysis of data from our experimental collaborators and development and application of bioinformatics software to genomic datasets. This includes processing data from a
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research, development, and analysis of data from our experimental collaborators and development and application of bioinformatics software to genomic datasets. This includes processing data from a
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(Python) and deep learning frameworks (PyTorch) with a drive to enhance these skills. Familiarity with one of the AI/ML fields like Natural Language Processing, Computer Vision, Reinforcement Learning
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assistant professor or associate professor whose research advances parallel and high-performance computing. Relevant areas include computer architecture, operating systems, compilers and the
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Genomics at Harvard Medical School Several positions are available in the Park Lab ( https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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) and the Martinos Center for Biomedical Imaging (Harvard/ MIT /Mass General). In parallel, there will be opportunities to analyze and publish existing data upon identifying areas of mutual interest