Bioinformatics.org
Not logged in
  • Log in
  • Bioinformatics.org
    Membership (42572+) Group hosting [?] Wiki
    Franklin Award
    Sponsorships

    Careers
    About bioinformatics
    Bioinformatics training
    Bioinformatics jobs

    Research
    All information groups
    Online databases Online analysis tools Online education tools More tools

    Development
    All software groups
    FTP repository
    SVN & CVS repositories [?]
    Mailing lists

    Forums
    News & Commentary
  • Submit
  • Archives
  • Subscribe

  • Jobs Forum
    (Career Center)
  • Submit
  • Archives
  • Subscribe
  • Career Center - Message forums

    Opportunity: Recruiting post-doc or research scientist in bioinformatics, Tao Wang Lab @ UT Southwestern Medical Center -- Dallas, TX (US)
    Submitted by Tao Wang; posted on Wednesday, April 14, 2021

    DESCRIPTION

    Lab introduction:
    The University of Texas Southwestern Medical Center (UTSW) is an elite research institution, with ongoing support from the National Institutes of Health and other federal agencies, foundations, individuals, and corporations providing more than $360 million per year to fund research. The faculty includes many distinguished members who have inspired the development of the Medical Center over this time, including 6 Nobel laureates, 22 National Academy of Science members, 16 National Academy of Medicine members and 13 investigators in the Howard Hughes Medical Institute.

    The Tao Wang Lab is a well-established bioinformatics research group at UTSW. Statistics, informatics, medicine, and biology are the four integral pillars of Tao Wang Lab's interdisciplinary research program. Dr. Wang's group has been working on mining public and in-house high throughput data to achieve a deeper understanding of the immunology of various human diseases, with a heavy emphasis on cancers, and its implications for diagnosis, prognosis, and treatment. The core research interest of Wang Lab is in tumor immunogenomics, computational immunology, scRNA-seq data analyses. The ultimate goal is to impact the prognosis and treatment of patients suffering from cancers and other diseases, through modeling of high dimensional data, especially genomics data. Tao Wang Lab has published 51 papers in top journals, such as Science Immunology (2020, Lu et al), Cancer Discovery (2018, Wang et al), SMMR (2020, Park et al), Nature Methods (2021, Zhang et al), and Cell (2019, Zhu et al), since its establishment in 2016.

    At UTSW, there are great opportunities for scientists to collaborate with outstanding biomedical investigators and work on exciting research projects. UT Southwestern and the Tao Wang Lab provide a friendly, dynamic, collaborative, and integrative research and training environment with state-of-the-art facilities. UTSW is an Affirmative Action/Equal Opportunity Employer. Women, minorities, veterans and individuals with disabilities are encouraged to apply.

    Position Title:
    Staff or Postdoctoral Fellow (Bioinformatics/Biostatistics/Computer Science/Computational Biology)

    Duties & Responsibilities:
    The projects include (1) developing novel methods for analysis and integration of cancer genomics, proteomics, imaging and other forms of high-dimensional -omics data, and developing prediction models for patients' clinical outcomes, (2) assembling and statistical analyses of big clinical data, (3) creating databases and websites for management of big biological data. Application for independent funding under the support of the PI.

    Position Qualifications:
    Candidates should have a doctoral degree (or will have one soon) in either one of the following fields, including genetics/genomics, bioinformatics, computer science, biostatistics, computational biology or a related field.

    Lab website: qbrc.swmed.edu/labs[...]x.php
    Google scholar: scholar.google.com/cita[...]hl=en
    QBRC with which Wang lab is affiliated with: qbrc.swmed.edu

    Recent publications:
    (1) Probability of phenotypically detectable protein damage by predicted deleterious mutations: analysis of ENU-induced mutations in the Mutagenetix database. Nature Communications. 2017: We developed a novel statistical metric to measure the probability of phenotypically detectable protein damage by predicted deleterious mutations.
    (2) An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factor. Cancer Discovery. 2018: We developed a Bayesian model to dissect the tumor microenvironment of kidney cancers, and developed the first empirical stroma/immune gene signature for kidney cancers.
    (3) Somatic Mutations Increase Hepatic Clonal Fitness and Regeneration in Chronic Liver Disease. Cell. 2019: We developed a suite of bioinformatics pipelines for analyzing ultra-deep sequencing data, and deployed them to study the low frequency mutations in liver cirrhosis patients.
    (4) Tumor Neoantigenicity Assessment with CSiN Score Incorporates Clonality and Immunogenicity to Predict Immunotherapy Outcomes. Science Immunology. 2020: We developed a neoantigen quality-based metric to predict the responses of cancer patients to checkpoint inhibitor immunotherapies.
    (5) Mapping the Functional Landscape of T Cell Receptor Repertoire by Single T Cell Transcriptomics. Nature Methods. 2021: We developed a Bayesian model named Tessa that is capable of quantifying the associations between T cell receptors and T cell gene expression in various biological contexts.
    (6) Overcoming Expressional Drop-outs in Lineage Reconstruction from Single-cell RNA Sequencing Data. Cell Reports. 2021: We developed a Bayesian model to trace the single cell lineages based on variant information derived from scRNA-seq data.

    HOW TO APPLY

    Please send your CV to: Dr. Tao Wang (Tao.Wang[at]UTSouthwestern.edu). Please don't add compressed files (e.g. zip files) in the email attachment, which will be blocked by UTSW firewall.

    DEADLINE

    Until filled

    Expanded view | Monitor forum | Save place

    Start a new thread:
    You have to be logged in to post a reply.

     

    Copyright © 2021 Scilico, LLC · Privacy Policy