Statistical Geneticist Research

The Statistical Geneticist Research are highly trained scientific investigators who are specialists in both statistics and genetics. The Statistical Geneticist Research is training in both statistics and genetics is necessary, as the nature of the work is highly interdisciplinary. The Statistical Geneticist Research must be able to understand molecular and clinical genetics, as well as mathematics and statistics, to effectively communicate with scientists from these disciplines. Typical Statistical Geneticist Research spend much of their time working with computers, since much of the statistical analysis of data is now conducted using computer software instead of pencil and paper. The Statistical Geneticist Research is actively engaged in developing new statistical methods for problems that are specific to genetics.

Statistical Geneticist Research Responsibilities:

• Perform genome scale analyses with genotype, imputed, and/or sequence data from >1 million individuals.
• Use statistical genetic analysis methods to generate insights about human disease.
• Integrate diverse molecular data types with association results to interpret and prioritize candidate therapeutic targets.
• Critically review and provide input on analysis plans, results and summaries to ensure they are accurate and reliable. Identify potential problems and propose remedies or refinements.
• Use statistical genetic analysis methods to generate insights about human disease and diverse complex traits.
• Integrate and lead hypotheses generation from genetics and diverse datasets by employing sound statistical genetics and computational biology approaches.
• Work with external and internal data sources for various analytical approaches
• Develop and apply statistical genetics approaches to predict complex disease conditions using genomics and clinical data.

Statistical Geneticist Research Requirements:

• PhD in Human Genetics, Statistical Genetics, or a related field.
• Solid experience and competence with current approaches in genomic analysis.
• Strong Programming experience.
• Experience in biostatistics, linear/non-linear regression models, dimensionality reduction, clustering, and/or bayesian networks methods.
• Ability to develop, benchmark and apply predictive algorithms to identify novel biomarkers, dissect gene/disease relationships and generate hypotheses.

Statistical Geneticist Research – US & CanadaAre you looking for a Statistical Geneticist Research? Take a look at our Job Descriptions Board for US & Canadian businesses.