Open date: June 2nd, 2021
Next review date: Thursday, Jun 17, 2021 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Friday, Dec 2, 2022 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Human Microbiome Research
The UCSF Division of Gastroenterology, Department of Medicine seeks a computational biologist to join the Microbial Genomics Collaborative Laboratory (CoLab) at the Benioff Center for Microbiome Medicine (BCMM). Located at the University of California San Francisco, the BCMM houses the community of researchers on campus focused on leveraging the human microbiome to predict, prevent and treat disease. The successful candidate will work in partnership with the director of the Microbial Genomics CoLab to facilitate a range of research studies performed in collaboration with investigators across all four schools on campus. The successful candidate will be expected to contribute to study design and to apply bioinformatic and statistical tools to enable analysis of shotgun metagenomic, metabolomic, transcriptomic, immunologic and clinical data. Familiarity with integrative multi-dimensional data analysis is a significant advantage.
Candidates will be expected to work independently and efficiently multi-task. Those with the proven capacity to effectively communicate and a track record in productively contributing to collaborative multidisciplinary teams to support grant, manuscript and report preparation will be given preference. The successful candidates will report to Dr. Susan Lynch, Director of the Benioff Center for Microbiome Medicine and to Dr. Connie Ha, Director of the Microbial Genomics CoLab.
• Contribute to study design.
• Apply statistical tools to enable independent and integrated analyses of shotgun metagenomic, metabolomic, transcriptomic, immunologic and/or clinical data.
• Apply and develop bioinformatic tools as necessary for integrative analyses of multi-dimensional datasets.
• Present updates and findings at group and scientific meetings and contribute to manuscript preparation for publication in peer-reviewed journals.
• Contribute to research as part of a large multidisciplinary team.
• Specialists appointed at the Assistant or Associate rank must possess (or in process of obtaining) a Master’s degree in Bioinformatics, Statistics, Microbial Ecology, or a related discipline.
• Specialist appointed at the Full rank must possess (or in process of obtaining) a terminal degree (or equivalent degree) in Bioinformatics, Statistics, Microbial Ecology, or a related discipline.
• Applicants must have obtained the required degree for the appropriate rank by the time of hire.
• Knowledge and understanding of bioinformatics tools for metagenomic assembly, genome binning and strain-level genome reconstruction.
• Knowledge of bioinformatics tools for transcriptomic analysis including dual RNASeq analysis.
• Experience with relational databases, R, and other Unix tools is key.
Additional Desired Qualifications
• Demonstrated ability to work within a collaborative research team and effectively interact with a broad range of researchers from distinct disciplines.
• Ability to work independently and productively and to troubleshoot.
• Superb organizational and data management skills.
• Excellent written and oral communication skills and demonstrated capacity to accurately and effectively present projects to multi-disciplinary audiences.
Appointees in the Specialist series will be expected to engage in specialized research, professional activities and do not have teaching responsibilities. Specialists are expected to use their professional expertise to make scientific and scholarly contributions and may participate in University and Public Service. Appointment to a rank within the specialist series will be based on qualifications and experience:
Screening of applicants will begin immediately and will continue as needed throughout the recruitment period. Salary and rank will be commensurate with the applicants experience and training.
Please apply online at https://aprecruit.ucsf.edu/JPF03444. Applicants’ materials must list current and/or pending qualifications upon submission.
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. We especially encourage applications from those traditionally underrepresented in biological sciences.
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