School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,500 faculty physicians and researchers, more than 1,300 students, and more than 6,000 staff, the Duke University School of Medicine along with the Duke University School of Nursing, Duke University Health System and the Private Diagnostic Clinic (PDC) comprise Duke Health. a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.
The Duke University School of Medicine’s Department of Biostatistics and Bioinformatics consists of faculty and staff with expertise in bioinformatics—including for analysis of a wide variety of -omics data types—as well as biostatistics and medical informatics. The department is expanding its large and highly successful Biostatistics, Epidemiology, and Research Design (BERD) core to include Bioinformatics. The successful candidate will have a PhD in computer science, bioinformatics, biostatistics, or a closely related discipline, and will have experience with multiple bioinformatics data types and algorithms. The successful candidate will perform state-of-the-art bioinformatics analyses using existing pipelines and new pipelines composed of existing tools, will collaborate with world-leading clinical and basic science researchers, and will develop new collaborations. It is expected that after a year the successful candidate also will recruit additional bioinformaticians and will build and direct a bioinformatics team within the BERD core. This work includes leading cross-functional project teams, including clinical investigators, quantitative scientists, and graduate students, and engaging in design, analysis and interpretation of data in conjunction with academic research programs across the university.
- Independently develop and manage new collaborations such as, submission of new grants that cover bioinformatics effort, development of new internal or external collaborative agreements that cover bioinformatics effort.
- Estimate and negotiate accurate effort/time needed for projects and ensure projects that have delivered agreed-upon end products on time with the high quality.
- Collaborate with clinical and translational investigators to develop and support appropriate research teams to meet the needs of the School of Medicine.
- Work with collaborators to develop a clear understanding of the scope of a project/task, expected deliverables, and develop strategies to address challenges in the research process.
- Use analytical, algorithmic, and scientific understanding to propose and perform analyses and independently write the methods and analysis sections of reports/manuscripts.
- Follow institution guidelines, utilize good clinical and basic science research practice, and identify relevant regulatory requirements for agencies such as FDA, ICH, NIH, etc., and associated reporting requirements.
- As appropriate, develop guidelines and processes to ensure the highest level of quality and efficiency.
- Learn, implement, and stay knowledgeable about state-of-the-art methodologies
- Seek guidance for analyses when appropriate, but generally only consult faculty expert on an as-needed basis.
- Lead the analytical team responsible for designing and validating data sets, programs, and output products.
- Recruit, interview, onboard, train and supervise new staff who are hired to fill negotiated collaboration agreements.
- Conduct data management and appropriate analysis, create reproducible and transparent code, check and/or verify results (QC) based on provided specifications, learn about new data structures and train and supervise junior bioinformaticians to perform these tasks.
- Train and supervise junior bioinformaticians to clearly communicate about scientific questions in the context of research, learn and apply standard and state-of-the-art bioinformatics methods,
follow guidelines, collaborate through the research process, and to write methods and analysis sections.
Position requires a Doctoral degree in (bio)statistics or relateddegree.
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