Biostatistician

Description

The Center for Population Neuroscience and Genetics at the Laureate Institute for Brain Research is seeking talented and highly motivated data scientists for a biostatistician to create R scripts to format consortium data for integrated statistical analyses and to implement analytical procedures.

The profile of research organization

Laureate Institute for Brain Research (LIBR) has been a pioneer on the mind-body interaction and how it relates to psychiatric symptoms. With the newly founded the Center for Population Neuroscience and Genetics (PNG), we are positioned to use the large-scale population data, including biobanks, national registries, and deep-phenotyped population cohorts, to investigate the etiology of neurodevelopmental disorders, finding the potential pathways for clinical interventions.

Position

Dr. Wesley Thompson is currently seeking a biostatistician who possesses experience in large scale data wrangling and analysis. The Statistician, under the direction of Dr. Thompson, will program statistical analyses using the R programming language. This will include formatting and processing multi-modal, longitudinal data for integrated statistical analyses and producing data QC reports. Statistician analyses implemented will include mixed-effects models, latent variable models, dimension reduction algorithms, prediction models, and survival models.

The statistician will work as part of a multi-institution team to develop and apply advanced statistical methods for analyzing multimodal neuroimaging and genetic data, with the goal of understanding the complex interplays between the brain and environment in the context of human development. This position provides unique experience with longitudinal data aimed at understanding how the brain develops and is affected by exposure to substances and other environmental, social, and biological factors during pregnancy and after birth. What we learn from this research will have lasting impacts on future generations of children.

Qualifications

Necessary qualifications

• A relevant degree or equivalent qualifications.
• Experienced in computational language, either R or Python
• Background in applied statistics and high-dimensional data analytics

Preferred qualifications

• Excellence in large scale, population level data analysis
• Experience in developing methods for high-dimensional data
• Experience in analyzing multivariate longitudinal and survival data
• Experience in Neuroimaging and Genomics
• Experience in developing methods for high-dimensional data analysis

Personal qualifications

• Strong drive to obtain established goals
• Excellent collaborative, communication, and presentation skills
• Scientifically self-motivated and creative
• Ability to work both independently and in structured groups
• Open-minded and analytical personality