Computational Biology Data Scientist
The Quantitative Sciences Unit (QSU) is an interdisciplinary collaborative statistics unit in the Biomedical Informatics Research Division within the Department of Medicine at Stanford University. The mission of the QSU is to facilitate cutting-edge scientific studies initiated by Stanford investigators by providing expertise in biostatics and informatics, to mentor and educate clinical investigators in research methods and to mentor data scientists. To optimally achieve this mission, the QSU members become fully integrated into individual research teams.
The QSU is seeking a highly motivated, hard-working and professional computational biology data scientist to extend our team of collaboration with clinical, immunological and bioinformatical researchers. We generate and have access to clinical and immunological data as well as many large data sets, including mass cytometry (CyTOF) and single cell sequencing data. The successful candidate will join a vibrant team of academic statisticians working on a wide variety of collaborative projects in medicine. This position holds excellent career development opportunities. This is an academic staff fixed-term position.
- Take the statistical lead on studies including; designing the study, the analysis plan and carrying out the statistical programming and data management to implement the plan.
- Experience in single cell data analyses and integrative multi-omics approaches is a strong plus.
- A background in immunology and experience working with clinical trial data will be a plus and will help in the development of independent research projects.
- Oversee junior-level biostatisticians on data cleaning and creation of analytic files and mentor junior-level biostatisticians in the area of conducting collaborative research.
- Lead statistical projects related to collaborations on topics including the evaluation of statistical software or methods as well as the development of novel methods, as need arises within QSU collaborative projects.
- Collaborate with clinical and lab-based investigators on campus including the Heart Center, the Department of Medicine, the Department of Neurosurgery, and the Stanford Cancer to independently design studies and develop analysis plans. More specifically, the incumbent will meet one-on-one with the collaborator to gain background on the study and the research questions and help to refine the questions and formulate the hypotheses. The incumbent will also extract necessary information to design the study with optimal operating characteristics and to develop a sound statistical plan.
- Develop oral and written dissemination of findings for meetings with collaborators or for medical and/or statistical journal articles. The incumbent is also expected to develop lectures on statistical methods or statistical programming for the training of clinical investigators as needed and for the training of junior biostatisticians. In addition, the incumbent will participate in developing and writing grant proposals.
- Ph.D. in Computational Biology, Biostatistics, Statistics, Bioinformatics or related field.
- Capable of functioning independently and collaboratively at an advanced level under the overall direction of the QSU Director.
- Experience with multiple statistical programming languages such as SAS and R.
- Outstanding oral and written communication skills with the ability to communicate technical information to all audiences.
- Skilled in descriptive analysis, modeling of data, and graphic interfaces.
- Demonstrated expertise in statistical methodology.
- At least five years of experience collaborating as a computational biologist or biostatistician is desirable.
- Certification in SAS.
- Experience supervising technical staff including training, mentoring and coaching.
- Experience developing and writing grant proposals.
*- Stanford University is an equal opportunity employer and is committed to increasing the diversity of its faculty and academic staff. It welcomes nominations of and applications from women and members of minority groups, as well as others who would bring additional dimensions to the University’s research, teaching and clinical missions.
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