Soc/Clin Research Manager

Job description

Position Type:

Permanent Staff (SHRA)

No

Soc/Clin Research Manager - Advanced

Soc/Clin Research Manager

20014467

P012362

$80,000-$99,000

To learn more about the pay band for this branch and role, please see the Career Banding rates spreadsheet.

GN17

Full-Time Time-Limited

40

Monday-Friday, 8am-5pm

ESE - Inst Envir Hlth Solution-463003

02/11/2021

02/26/2021

Chapel Hill, NC

Research Professionals

The Department of Environmental Sciences and Engineering (ESE) in the School of Public Health at the University of North Carolina at Chapel Hill is one of the oldest, largest, broadest, and best programs of graduate education and research in the field. ESE was founded in 1923 and has evolved over the years to include currently 30 faculty members, a total of 43 emeritus and adjunct faculty members, 18 post- doctoral research associates, and 140 graduate students. The Department has total overall annual expenditures over $14 million and has endowed funds in all categories of $10 million. The primary purpose of the department is the education of students in the area of environmental sciences and the pursuit of research in the same filed to further educate students and provide areas of development in the field in collaboration with stakeholders such as local, national, and international communities.

The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran.

THIS IS A TIME LIMITED POSITION

The Biostatistician will become a key member of a dynamic research team by providing critical research expertise for complex high-dimensional data analysese in biomedical / environmental health research that includes:
developing novel advanced statistical methods, such as graphical models, and bioinformatics pipelines to process, analyze, annotate and illustrate high-dimensional data, (2) analyzing large complex omics/high-throughput research data (e.g., genomics, epigenomics, metabolomics, exposomics and microbiobiome sequencing data), (3) discovering and proposing new research hypotheses through data mining, (4) contributing to research activities such as writing grant proposals, (5) reporting research results in posters and manuscripts, (6) presenting data and information to the research team, and (7) serving as a research contact for students and postdoctoral trainees.

Major responsibilities will include supervising experimental design, data collection and data management, developing and establishing new statistical methods and bioinformatics pipelines for high-dimensional genomics, epigenomics, metabolomics and exposomics data, discovering new research hypothesis using data mining strategies, performing statistical analyses of high quality, accuracy and consistency for research projects, writing and revising research proposals and grants, statistical power calculations, and training/advising students and postdoctoral researchers on statistical methods and data analyses. The sucessful candidate will have strong statistical computational background and expertise in analyzing high-dimensional genomics, epigenomics, metabolomics, exposomics and microbiome data to support research activivites of the team.

Master’s degree in a discipline related to the field assigned; or Bachelor’s degree in a discipline related to the field assigned and two years of research/analysis, preferably with one year in a supervisory role; or equivalent combination of training and experience. All degrees must be received from appropriately accredited institutions.

- Expertise in a range of advanced statistical methodologies with application to high-dimensional data analysis;
- Demonstrated expertise in statistical analysis for large data sets related to biomedical and/or environmental health research;
- Excellent skills in programming in several languages, including SAS and R, in complex data analyses;
- Experience in analyzing omics data, including genomics, epigenomics, metabolomics, exposomics and microbiome data;
- Experience in writing grant proposals and manuscripts;
- Experience in advising and training students and consulting research projects;
- Excellent written and oral communication skills for research presentations.

It is preferred that the incumbent possess a PhD in Statistics, Biostatistics, or a related field; have a capacity for learning new technical skills independently; possess excellent written and oral communication skills; and have outstanding programming skills (R and SAS preferred) for omics data analysis.

No

Share this job with your network: