Manager, Biostatistics DOM Channing

The Channing Division of Network Medicine, Brigham and Women's Hospital, and Harvard Medical School are seeking a Research Biostatistics Manager to contribute to the RECOVER Systems Biology Initiative, led by Associate Professor Jessica Lasky-Su. The RECOVER Long COVID initiative aims to understand, prevent and treat incidence of chronic effects of COVID-19. Working closely with Associate Professor Jessica Lasky-Su, and Research Operations Manager will be responsible for integrating multi-omic data (genomics, epigenetics, proteomics, transcriptomics, metabolomics, electronic health record data) from both clinical data and research population, using advanced computational methods such as deep learning. The candidate is expected to have a proven track record of research with analysis supporting high impact scientific publications.

The Channing Division of Network Medicine represents a diverse and highly collaborative research community that is focused on deciphering the etiology of complex diseases. The lab benefits from active collaborations with computational, biostatistical, and networking experts. We also work with state-of-the-art laboratories for the generation of 'omics' data and have established bioinformatic pipelines for cleaning and preparing data for analysis. The Research Biostatistics Manager will primarily be working on statistical analysis, developing new scientific initiatives and scientific write up of projects based on the RECOVER Systems Biology Initiative, which will have a wealth of multi-omic data and cover lifestyle, behavior, dietary and environmental risk factors. These outstanding resources offer the potential for a high-quality candidate to address scientific questions of interest and clinical outcomes. We are seeking highly motivated and analytically-capable applicants who have a strong interest in progressing the field through impactful science.

PRINCIPAL DUTIES AND RESPONSIBILITIES:

• Prior experience working with phenotypic and OMIC datasets that include at least one of the following: genetics, transcriptomics, epigenetics, proteomics, or metabolomics.
• Ability to apply statistical and machine learning techniques to large clinical variables and OMIC data setsExperience in Programming with R, Python, MATLAB, and/or Java that focus on computational biological applications for clinical data
• Prepare detailed quality control report workflows for evaluation by principal investigators and other staff members. Perform complete data validation and error detection; ensuring data security, integrity measures are met. Discuss with researchers to discuss results, analysis direction prior to project.
• To work closely with genetic epidemiologists and biological laboratories to administer and support solutions to cutting edge problems in the creation and interpretation of data creation.
• Contribute in the preparation of scientific methods for manuscripts detailing methods and design; Presentations of results.
• Manager of team of (2) Biostatician /Bioinformation ensures best practices regarding programming skills and help them understand data complexities, day to day management responsibilities
• Performs all other duties/responsibilities as directed.

Qualifications

QUALIFICATIONS:

PhD in Computer Science, Epidemiology, or a biological science required. Applicants will have 5+ years of programming experience developing software solutions for computational, biological or engineering problems. Understanding of clinical data validation recommended.

SKILLS/ ABILITIES/ COMPETENCIES REQUIRED:

• Prior experience working with omic datasets that include at least one of the following: genetics, transcriptomics, epigenetics, proteomics, or metabolomics.
• Experience developing novel methods for complex data integration of omic data
• Ability to work in a highly collaborative and intellectually challenging environment. Perform the technology watch; contribute to the strategy and evolution of existing services, as well as future architecture evolution around communication platforms
• Must work independentlyStrong analytic background in genomics, bioinformatics, statistics, epidemiology, computer science, network biology or related field. Understanding of epidemiological concepts and the relevant statistical analyses
• Excellent oral and written communication skills to write and contribute to scientific publications.
• Proven scientific publications in peer-reviewed journals is necessary. Excellent written and verbal communication skills are essential. Ability to work in a highly collaborative and intellectually challenging environment.
• Must work independently.Excellent oral and written communication skills.

EEO Statement

BWH is an Affirmative Action Employer. By embracing diverse skills, perspectives and ideas, we choose to lead. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.