Senior Biostatistician

Key Skills

Biostatistics, Data Analysis, Data Modeling, Design, Effective communication skills, Linux Operating system, MySQL, R Programming, SAS, SPSS Statistics, statsmodels

Job Description

This position has the flexibility to be either (1) based on the Stanford campus, (2) hybrid between working on-site and working from home, or (3) fully remote.

The Department of Molecular and Cellular Physiology is seeking a dynamic, independent, and creative Senior Biostatistician (Biostatistician 3) to join the Huttenhain Laboratory to study how signaling receptors, specifically G protein-coupled receptors, decode extracellular cues into dynamic and context-specific cellular signaling networks to elicit diverse physiologic responses. You will develop computational and statistical methods to analyze and visualize quantitative proteomics data and integrate these with other high-throughput datasets generated in house or publicly available. The ideal candidate would join the team in August 2023 or shortly after. 

Lab overview: The communication between cells and their environment depends on a finely tuned decoding of extracellular cues into an array of intracellular signaling cascades that drive a cellular response. These signals are integrated through highly dynamic and context specific signaling networks that collectively define the phenotypic output. Given the complexity and dynamic state of signaling networks, the current understanding of their constituents and how they are spatiotemporally regulated as a result of a specific input is incomplete.

The Huttenhain lab studies mechanisms of intracellular signal integration through G protein-coupled receptors (GPCRs) by employing an interdisciplinary approach to probe, model, and predict how signaling network dynamics translate extracellular cues into specific phenotypic outputs. Developing quantitative proteomics approaches to capture the spatiotemporal organization of signaling networks and combining these with functional genomics to study their impact on physiology, we aim to better understand GPCR signaling and provide a solid foundation for the design and testing of novel therapeutics targeting GPCRs with higher specificity and efficacy.

Job description: You will take the lead on setting up the computational data analysis infrastructure for the Huttenhain lab, with specific focus on quantitative proteomics data and their integration with other high-throughput datasets, such as functional genomics. You will develop and apply appropriate algorithms, computational techniques, and statistical methodologies to analyze and visualize data primarily generated through high-throughput experiments. In-house data types will focus on quantitative proteomics for protein abundance, post-translational modifications, protein-protein interaction, or spatial protein organization. Data analysis will include quality control, normalization, statistical tests, correction for multiple testing, as well as further downstream analyses including functional or kinase enrichment analysis, network analysis, and integrating results from varied experiments. In addition to taking computational lead on studies, you will work with lab members and collaborators to aid in experimental and statistical design of projects, and in the biological interpretation and integration of the resulting complex data sets. Furthermore, you will train lab members in computational analysis and evaluation of their datasets.

The candidate should have experience with computational and statistical methods; high level of initiative and motivation; ability to work independently and with a team; excellent communication, organization, and time management skills; creative thinking and passion for science.

The Huttenhain lab is a supportive and interdisciplinary workplace that provides exposure to innovative research and cutting-edge technologies. This position is a unique opportunity to set up a new laboratory, for scientific growth and development with the potential for widespread recognition of scientific contributions.

Duties include:

• Set up and maintain the computational data analysis infrastructure in the Huttenhain lab.
• Develop and/or apply novel data analysis and statistical strategies.
• Providing advice on study design and development.
• Providing advice on and assistance with the development of analytic plans.
• Providing advice on and assistance with sample size and power calculations.
• Performing and assisting with data analyses.
• Assisting with the graphical presentation of data.
• Assisting with the use of statistical software.
• Helping with database development and documentation.
• Authorship and editing of statistical methodology sections for grant applications, study proposals, and manuscripts.
• Conducting training for lab members on computational analysis.

* - Other duties may also be assigned

DESIRED QUALIFICATIONS:

•  Strong computational skills and knowledge in programming, statistics, biology.
• Experience with statistical analysis and visualization of results using the R programming language, or another language (Python, Matlab, etc.) and willingness to learn R.
• Experience with large-scale proteomics data and placing it in a biological context, experience with other -omics data such as transcriptomics, lipidomics, and metabolomics and their integration desired.
• Familiarity with biological networks, their analysis and display.
• Application and validation of machine learning methods to complex data.
• Prior experience with Unix/Linux environments.
• Excellent communication skills; will and ability to interact with all levels of staff, external contacts, students, trainees, and collaborators.
• Enthusiasm, curiosity, and eagerness to learn and develop, collaborate and contribute to an inclusive and supportive environment.

EDUCATION & EXPERIENCE (REQUIRED):

Master's degree in biostatistics, statistics or related field and at least 5 years of experience or Ph.D. in biostatistics, statistics or related field.

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; 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).

PHYSICAL REQUIREMENTS*:

• 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.

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS:

May work extended or non-standard hours based on project or business cycle needs.

WORK STANDARDS:

• 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.

This role is open to candidates anywhere in the United States. Stanford University has five Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range for this position is $111,000 to $165,000 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.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.