Job Number: 75429
A research lab in the Division of Biomedical Informatics Research and the Institute for Immunity, Transplantation and Infection at Stanford School of Medicine is seeking highly motivated individuals for multi-disciplinary research in computational immunology. The projects will utilize diverse cohorts generated using state-of-the-art technologies across one or more diseases. These individuals will work with, and lead teams of postdocs and graduate students focused on an immunological disease. The Biostatistician 2 will with some independence, consult with investigators to refine research questions, define hypotheses, design studies and devise analysis plans, work with senior Statistician(s) to implement analysis plan and publish findings.
- Design study.
- Develop and implement protocol for quality control.
- Create analytic files with detailed documentation.
- Select appropriate statistical tools for addressing a given research question.
- Implement data analysis through statistical programming.
- Present results for investigators using graphs and tables.
- Summarize findings orally and in written form.
- Participate in the preparation of papers for publication.
- Consult with investigators on appropriate statistical approaches to data analyses; assist in study design and proposal development.
- Mentor collaborators in areas of experimental design, quality control, and statistical analysis.
- Develop oral and written dissemination of findings for conference presentations and peer-reviewed journal articles.
- Oversee lower-level staff on issues related to quality control and creation of analysis files.
- PhD in immunology, computer science or biostatistics
- Strong background in machine learning, biostatistics and bioinformatics
- Experience with various experimental technologies in immunology including but not limited to flow cytometry, tetramer, and repertoire sequencing
- Experience with analysis of sequencing data
- Manipulation and analyses of complex high-dimensional data
- Experience with deep learning approaches
- Industry experience as a data scientist
- Demonstrated ability to implement machine learning models in scalable format for broad applicability
- Strong communication and presentation skills
Master's degree in biostatistics, statistics or related field and at least 3 years of experience.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Proficient in at least two of R, SAS, SPSS, or STATA.
- Skills in descriptive analysis, modeling of data, and graphic interfaces.
- Outstanding ability to communicate technical information to both technical and non-technical audiences.
- Demonstrated excellence in at least one area of expertise, which may include coordinating studies; statistical methodology such as missing data, survival analysis, statistical genetics, or informatics; statistical computing; database design (e.g., expertise in RedCAP or MySQL); graphical techniques (e.g., expertise in Illustrator).
- Frequently perform desk based computer tasks, seated work and use light/ fine grasping.
- Occasionally stand, walk, and write by hand, lift, carry, push pull objects that weigh up to 10 pounds.
May work extended or non-standard hours based on project or business cycle needs.
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu.
Job: Information Analytics
Location: School of Medicine
To be considered for this position please visit our web site and apply on line at the following link: stanfordcareers.stanford.edu
Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.