The Gladstone Institutes is an independent, not-for-profit research organization affiliated with the University of California San Francisco (UCSF), contributing to the health and well-being of all people through medical research, education, and outreach in the areas of heart disease, HIV/AIDS, and neurological disease. Gladstone Bioinformatics as part of the Institute of Data Science and Biotechnology hosts a convergence zone of cutting-edge research, omics analytics, biostatistics and technology development, and is one of the primary centers for the NIH-sponsored National Resource for Network Biology. We are located in an award-winning building adjacent to UCSF's vibrant and active Mission Bay Campus. In addition to daily seminars and learning opportunities, our campus includes a gym, farmer’s market, advanced medical facilities, biotechnology corridor, food truck court, etc. Flexible telecommuting options are available for this position.
We are seeking a talented Bioinformatician or Statistician at either junior or senior levels to join the dynamic bioinformatics team here at Gladstone Institutes. You will be providing bioinformatics and computational support to the world-class biomedical research conducted in labs at Gladstone Institutes, UCSF, and beyond. Working closely with experimental scientists, you will collaborate on end-to-end studies from hypotheses and experimental design, to analysis plans, implementation and pipelining, to methods assessment and publication. You will be working with a variety of data types generated by various platforms and technologies (e.g., genome sequencing, bulk and single cell RNA-seq, ChIP-seq, ATAC-seq, HiC, metagenomics, CRISPR screens, mass spectrometry, and others). You will have opportunities for teaching, authorship, methods development, grant writing and training to further develop your expertise and skill sets.
MS or PhD with experience in Bioinformatics/Statistics (or similar quantitative fields) preferred. Demonstrated experience with analysis of any type of sequence data, large biological datasets using R, Python or equivalent is required. Statistical genetics experience or experience modeling various biological data types is strongly preferred. Prior consulting or industrial experience supporting research is a plus. The successful candidate will have a strong background in computational science, statistical analysis, experimental design, and quantitative analysis of biological systems, as well as a demonstrated ability to communicate and work effectively with all types and background levels of internal and external collaborators.
Salary: Based on experience.
Start Date: 2021
Please submit the following:
Cover letter (optional)
Contact info for 3 references (can be submitted later)