Senior Biostatistician (Computational Exposomics) - Rollins School Of Public Health

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Description:

JOB DESCRIPTION:

• Develops and analyzes a variety of research data using statistical methods.
• Assists researchers in developing appropriate study protocols and computer analyses.
• Manages computer systems, writes programs, and trains others in the use of systems.
• Keeps abreast of the latest statistical modeling and computing tools.
• Participates in the development and selection of appropriate statistical methods and tests, sample size calculations and creation of randomization schedules.
• Prepares statistical method sections for inclusion in study protocols.
• Reviews the design and content of database designs and data edit checks.
• Develops and validates SAS programs to support statistical analyses.
• Provides interpretations of statistical results, and prepares the relevant statistical sections for study reports.
• Creates and maintains biostatistical documentation, including descriptions of methods, SAS programs and results.
• Prepares electronic files using appropriate formats for submission to regulatory agencies.
• Participates in the development of standardization procedures for statistical functions.
• Reviews and audits statistical analysis plans, SAS programs, and statistical reports including tables, listings, and figures.
• Provides guidance to more junior biostatisticians.
• Evaluates and proposes new statistical methods for data analysis.
• Assigns and monitors activities of other project personnel.
• Assist in setting priorities of work to be done.
• Provides support and serves as a resource to biostatisticians, programmers, and data analysts.
• Participates in training of less Senior Biostatisticians and other team members.
• Provides input into the evaluation of their team members.
• Reviews and helps prepare statistical and database management sections of NIH grant applications and other externally supported proposals prior to submission.
• Writes statistical methods section of manuscripts for publication.
• Writes and/or revises quantitative, epidemiologic, and medical sections of manuscripts.
• Helps estimate budgets for biostatistical support for larger, more involved clinical studies (NIH program project grants, multicenter clinical trials etc).
• Monitors data collection, institutes procedures to assure data quality and guarantees study protocols are followed appropriately.
• Performs related responsibilities as assigned.

MINIMUM QUALIFICATIONS:

• A master's degree in statistics, biostatistics, computer science, or a related field and three years of experience as a biostatistician, preferably in an academic setting, OR an equivalent combination of education, training, and/or experience.
• Proficiency in modern high level statistical languages such as S-PLUS or SAS and in database management.

PREFERRED QUALIFICATION:

• The ideal candidate must have training in metabolomics, epidemiology, engineering, biostatistics, data science, bioinformatics or other environmental health related fields.
• Previous experience with big data analysis or omics is preferred.
• Experience with R or an equivalent programming language is preferred.
• Strong organizational and time management skills, with the ability to independently meet project timelines is preferred.
• While preference will be given to candidates with the expertise summarized above, we are willing to train exceptionally motivated individuals with strong analytical and communication skills.
• Candidates will have hands-on experience working with exposome studies and have the opportunity to learn fundamentals of untargeted mass spectrometry data acquisition and analysis, pre-processing workflows, EWAS and characterization and interpretation of results.

ADDITIONAL JOB DETAILS:

 

The Comprehensive Laboratory for Untargeted Exposome Science (CLUES) in the Gangarosa Department of Environmental Health at Emory University seeks talented applicants with expertise in biostatistics, epidemiology, environmental health, data science and/or systems biology to join a growing research group that leverages state-of-the-art mass spectrometry platforms to measure the human exposome. These efforts have enabled new methods for significantly advancing the ability to characterize how exposures contribute to disease, and now provide a precision environmental health framework for studying the intersection of environment, biology and disease at the population level. We are an internationally recognized laboratory in the emerging field of exposome research and provide ample opportunities for training in cutting edge high-resolution mass spectrometry methods that explore exciting research questions at the interface of environment, multi-omics and human health. The ideal candidate will have experience coding in R or Python, and be willing to apply cutting-edge biostatistics and data science approaches for solutions in computational mass spectrometry, metabolism, and exposome-wide association studies (EWAS) in support of ongoing research projects. This position will support data analysis and management needs for a large range of research projects. Areas of study include environmental determinants of non-communicable diseases (cancer and other metabolic diseases), measuring complex exposures of emerging concern, including microplastics, PFAS, and e-waste, and establishing OMIC-based strategies for universal chemical surveillance and bioeffect monitoring. The facility currently houses two LC-HRMS (Thermo Exploris 120 Orbitraps) and three GC-HRMS (2 Thermo GC Q-Exactive and 1 Thermo GC-Exploris Orbitraps) and has plans to strengthen its technology base further. The exposome provides a new paradigm for understanding how complex exposures drive adverse health outcomes, and candidates will have the opportunity to be at the forefront of technological and data science methods for this emerging field of research.

 

Responsibilities may include:

• Coding and data manipulation in R, Python or equivalent languages.
• Optimization and management of bioinformatic workflows for data extraction, processing and annotation of untargeted mass spectrometry data.
• Apply variable selection techniques based upon univariate and multivariate approaches.
• Perform EWAS for disease and adverse health outcomes.
• Database development for creating a cumulative resource of untargeted exposome studies.
• Organize and manage study meta-data.
• Establish and manage a FAIR data structure for untargeted mass spectrometry data.
• Provide summaries and interpretation of untargeted exposo

Our laboratory is located within the Rollins School of Public Health at Emory University. The Rollins School of Public Health is ranked 5th among Public Health graduate schools by U.S. News & World Report and ranked number 5 in the Blue Ridge Report amongst schools of Public Health receiving NIH support. The Gangarosa Department of Environmental Health houses researchers with interests spanning Environmental Health, including mechanistic and computational toxicology, genomics, the developmental origins of disease, air pollution, climate change, water, sanitation and hygiene, and environmental epidemiology. Within the department is Emory’s HERCULES Health and Exposome Research Center, an NIEHS P30 Environmental Health Support Center and the first Exposome Research Center in the US. The team science approach in this department provides opportunities to co-author publications with leading collaborators. We offer numerous opportunities for career advancement, including the ability to attend workshops on topics related to the exposome and data science, and travel to national and international conferences. Work-related experience will be considered in determining level and salary.

 

NOTE: Position tasks are generally required to be performed in-person at an Emory University location.  Remote work from home day options may be granted at department discretion. Emory reserves the right to change remote work status with notice to employee.

 

Emory Supports a Diverse and Inclusive Culture:

Emory University is dedicated to providing equal opportunities and equal access to all individuals regardless of race, color, religion, ethnic or national origin, gender, genetic information, age, disability, sexual orientation, gender identity, gender expression, and veteran's status. Emory University does not discriminate in admissions, educational programs, or employment on the basis of any factor stated above or prohibited under applicable law. Students, faculty, and staff are assured of participation in University programs and in the use of facilities without such discrimination. Emory University complies with Executive Order 11246, as amended, Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veteran's Readjustment Assistance Act, and applicable executive orders, federal and state regulations regarding nondiscrimination, equal opportunity and affirmative action. Emory University is committed to achieving a diverse workforce through application of its affirmative action, equal opportunity and nondiscrimination policy in all aspects of employment including recruitment, hiring, promotions, transfers, discipline, terminations, wage and salary administration, benefits, and training. Inquiries regarding this policy should be directed to the Emory University Department of Equity and Inclusion, 201 Dowman Drive, Administration Building, Atlanta, GA 30322.

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