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for a postdoctoral fellow position in the Laboratory of Systems Pharmacology ( LSP ; https://labsyspharm.org/ ), part of the Harvard Program in Therapeutic Science, at Harvard Medical School in
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and Machine Learning , with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable
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methods to compare the genetic architecture of rare vs. common genetic variation 2. Developing methods to analyze GWAS data using graphical models and genome-wide genealogies 3. Developing methods to
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images contain rich information on complex diseases. The goal of our efforts is to build and apply automated analytical pipelines for various types of pathology data, including histopathology images and
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Perrimon’s group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post-doc trainees in
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. Norbert Perrimon’s group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post-doc
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Fellow to develop and evaluate artificial intelligence methods for physical medical procedures. The fellow will design and implement machine learning models to analyze procedural data, support clinical
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academic year. For history of the chair, see https://harvaus.fas.harvard.edu/ Incumbents of the Chair will ordinarily hold the title of Gough Whitlam and Malcolm Fraser Visiting Professor of Australian
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the SMaHT Data Analysis Center that manages multi-omic data (e.g., Illumina/PacBio/ ONT Whole Genome Sequencing ( WGS ), RNA -Seq). The ideal candidate will have a deep understanding of next
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analysis pipelines for processing RNA -seq, single-cell RNA -seq, genomics, and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are