Computational Biology Data ScientistSchool of Medicine, Stanford, California, United StatesResearchFeb 08, 2023 Post Date97863 Requisition #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.Duties include:
- Take the computational biology 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 data scientists on data cleaning and creation of analytic files and mentor junior-level data scientists in the area of conducting collaborative research.
- Lead methodological projects related to collaborations on topics including the evaluation of 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 analysis 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.
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. REQUIRED:
- 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 programming languages such as Python 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 analytic tools.
- At least five years of experience collaborating as a computational biologist or biostatistician is desirable.
- Experience supervising technical staff including training, mentoring and coaching.
- Experience developing and writing grant proposals.
The expected pay range for this position is $106,000 to $133,000 per annum.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.Why Stanford is for You
Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:
- Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
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Stanford is an equal employment opportunity and 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, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University's research, teaching and clinical missions. Additional Information
- Schedule: Full-time
- Job Code: 6438
- Employee Status: Fixed-Term
- Grade: R99
- Requisition ID: 97863
- Work Arrangement : Hybrid Eligible