Job Description
Job Description
Location : REMOTE
Weekly Hours - FT : 30-40 hours per week Total No. of Hours : 40
Overall Position Summary and Objectives
We are seeking an experienced statistical geneticist with expertise in epigenetic data analysis. Working in collaboration with Drs.
Rick Woychick, Trevor Archer and Alison Motsinger-Reif, they will play a crucial role in advancing our understanding of the complex interplay between genetics, epigenetics, and the environment and its impact on human health and disease.
Responsibilities include :
Design implements statistical methodologies for analyzing large-scale epigenetic datasets, including DNA methylation, histone modifications, and chromatin accessibility
Develop apply advanced statistical models and algorithms to identify epigenetic marks associated with specific genetic traits, diseases, or environmental exposures
Min Education - Master's
Resume Max Pages - 3
Certifications & Licenses
The ideal candidate will have a Ph.D. in statistical genetics, biostatistics, bioinformatics, computational biology, or a related field with a strong emphasis on statistical analysis of epigenetic data.
They will need proven experience in applying statistical methods to large-scale genetic and epigenetic datasets, including DNA methylation, histone modifications, or chromatin accessibility.
Skills (Ranked By Priority)
They will need proven experience in applying statistical methods to large-scale genetic and epigenetic datasets, including DNA methylation, histone modifications, or chromatin accessibility.
They should be proficient in programming languages such as R and / or Python, as well as experience with relevant statistical analysis packages (e.
g., Bioconductor, PLINK, ChAMP, or similar).
1, 2, 3, 4, 5 represents priority rankings, where 1 is highest priority and 5 is lowest priority of those ranked
Software
R / Python and Plink with other command line genetic tools.
Field of Study
- Genetics
- Statistics and Decision Science
Statement of Work Details
Assists in performing a variety of data management and analytical tasks and organizing complex, large-scale datasets.
- Provide biostatistical expertise for the research study.
- Analyze, interpret, communicate and document epidemiologic data and results.
- Provide analytic results using standard statistical procedures, including descriptive statistics, rate standardization, stratification of data and model building (logistic regression, conditional logistic regression, Cox regression) using SAS, Stata, Epicure, and similar statistical software programs.
- Collaborate and work with a team of researchers to develop, iterate and execute innovative strategies for genomic data integration and modelling / prediction.
Utilizes statistical software packages to manage, maintain and analyze large, complex statistical datasets.
- Applies a variety of data reduction techniques.
- Design and implement statistical methodologies for analyzing large-scale epigenetic datasets, including DNA methylation, histone modifications, and chromatin accessibility. 1
- Develop and apply advanced statistical models and algorithms to identify epigenetic marks associated with specific genetic traits, diseases, or environmental exposures. 2
- Collaborate with cross-functional teams to design and execute epigenetic research studies, providing statistical guidance and expertise throughout the research process. 3
- Perform data preprocessing, QC, and normalization of data, ensuring accuracy and reliability for downstream analysis.
- Conduct statistical analyses, including but not limited to differential methylation analysis, epigenome-wide association studies(EWAS), pathway analysis, and integrative analysis of genetic and epigenetic data.
- Interpret and communicate statistical results to both technical and non-technical stakeholders, including presenting findings in scientific publications, conferences, and internal meetings. 5
- Stay up-to-date with the latest advancements in statistical epigenetics, genomics methodologies, and data analysis techniques, and integrate them into the research and development process. 4
- Collaborate with bioinformatics teams to integrate genetic, epigenetic, and genomic data into computational pipelines and develop efficient workflows for analysis.
- Contribute to the development and maintenance of in-house statistical epigenetics software tools and resources.
- Mentor and provide guidance to junior researchers and data analysts, fostering a collaborative and intellectually stimulating environment.
- Provide project management for the large interdisciplinary project team.
Documents analyses performed and prepares progress reports summarizing results.
Write statistical sections in manuscripts; work with research staff to interpret referees' comments on manuscripts.
Performs a variety of data management and analytical tasks and organizing complex, large-scale datasets.
- Provide biostatistical expertise for the research study.
- Analyze, interpret, communicate and document epidemiologic data and results.
- Provide analytic results using standard statistical procedures, including descriptive statistics, rate standardization, stratification of data and model building (logistic regression, conditional logistic regression, Cox regression) using SAS, Stata, Epicure, and similar statistical software programs.
- Collaborate and work with a team of researchers to develop, iterate and execute innovative strategies for genomic data integration and modelling / prediction.
Conducts statistical analyses on completed and ongoing studies utilizing a wide range of standard and non-standard statistical software packages for all projects.
Write code to execute data analysis, visualize and provide interpretation and context to results of analysis.
Reviews and summarizes relevant literature and other sources to develop analytical plans.
Consult with staff on the application of statistical methods to address the key study scientific aims of the study.
Learns and applies new statistical methods and software packages and provides consultation and training to other analysts and staff.
- Research and analyze new developments in biostatistical methods and applications.