Bioinformatics Scientist

    The Mesirov Lab at UC San Diego seeks an exceptional candidate who is passionate about accelerating the pace of cancer research through the analysis of genomic data and making sophisticated computational methods available to the research community at large through advanced, accessible software tools. Research in the lab (www.mesirovlab.org) focuses on leveraging machine learning and statistical methods by applying them to functional genomics data derived from cancer patients and models to better understand the underlying biological mechanisms of disease, improve stratification of patients’ treatment outcome, and identify novel drug targets.

    The lab is also committed to the development of user-friendly open source software tools to bring these methods to the general biomedical research community. These tools have supported over 500,000 investigators worldwide. Thus, to achieve its goals, the lab includes computational biologists, bioinformatics scientists, and software engineers working together to further our understanding and treatment of disease.

    The bioinformatics scientist will work with other members of the Mesirov Lab and physician scientists at the UCSD Moores Cancer Center to address current challenges in improving the understanding of cancer and improving patient treatment. The position will also play an important role as a bridge between the cancer research community and the major software projects in the lab.


    Interested candidates should apply here


    Job Responsibilities

    • Analyze cancer genomics data for projects within the lab and with external collaborators using state-of-the-art algorithms and computational methods for analysis and interpretation of large and complex datasets.
    • Develop GenePattern notebooks (notebook.genepattern.org) that capture high impact analyses to ensure they are an effective tool for the biomedical research community.

    Minimum Qualifications

    • A Bachelor's Degree in Life Sciences, Bioinformatics, Computer Science or other related discipline.
    • Knowledge of computational methods and approaches, including prior experience with machine learning algorithms, data science, and statistics.
    • Driving interest in combining computational and biological knowledge to address biomedical challenges.
    • Experience with programming languages such as Python or R.

    Preferred Qualifications

    • Masters or PhD degree in Life Sciences, Bioinformatics, Computational Biology, or other related discipline; or a combination of education and experience.
    • Experience with gene expression analysis (bulk or single cell RNA-seq), epigenetic data, or other functional genomic data.
    • Strong machine learning and/or statistical analysis skills.
    • Experience developing and/or applying computational methods for genomic analysis.