1) Work effectively with faculty, project stakeholders, researchers, and bioinformatics collaborators to implement novel or adapt existing approaches to optimize upstream and downstream analysis and interpretation of biological data.
2) Lead the development of new software applications or the customization ofÂ existing applications to meet complex scientific project needs. Identify suitable datasets and methods to answer particular research questions
3) Perform data analyst functions that generate knowledge via data mining, visualization, or other analytics
4) Design and perform formal evaluation of informatics methods and products, staying up to date on new advances and developments in bioinformatics.
5) Provide mentorship, training, and instruction of other team members in the selection and use of bioinformatics tools, generating documentation as needed.
1) Advanced knowledge of research techniques or methods Ability to train others
2) Ability to correctly select and perform statistical tests for genomic data
3) Ability to independently plan and execute bioinformatics analyses and/or result validation
4) Ability to keep up with the research in the bioinformatics field and teach yourself new methods
5) Ability to interact with biologists during a scientific discussion
6) Ability to detect data quality problems and solve them
7) Excellent organization and communication skills with an emphasis on strong presentation skills (Strong verbal, written, and visual communication skills with the demonstrated ability to present complex technical concepts to varied audiences)
1) PhD with at least two years post-graduation
2) Master's degree with at least (5) five years relevant working experience in Bioinformatics, Computational Biology, Computer Science, Mathematics, or a related field.
1) Minimum of two years of hands-on experienceÂ with analysis of NGS data.
2) Knowledge in the development, optimization, automation, and operations support of analysis pipelines for high dimensional data including whole-genome, whole-exome, and RNA sequencing data.
3) Experience with Python.
4) Experience with other languages such as R, Golang, C/C++, or Java.
5) Familiarity with open source and commercial bioinformatics resources and software, such as GATK.
6) Experience working with Linux and/or Unix.
7) Experience with human genetics/genomics.
NOTE: When applying, all required documents MUST be uploaded under the Resume/CV section of the application
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