The Genuity Artificial Intelligence Research Institute (GAIRI) is seeking a highly motivated Biostatistician
The Genuity Artificial Intelligence Research Institute (GAIRI) is seeking a highly motivated Biostatistician to help pioneer the use of Causal Inference, and Probabilistic Programming in the biomedical sciences. The candidate will work closely with other members of Computational Statistics team at GAIRI to develop statistical machine learning methods to discover novel causal relationships within high-dimensional biomedical datasets to better understand disease etiology, identify novel drug targets, and discover biomarkers for use in precision medicine.
Given the multi-disciplinary nature of the position, strong collaboration and communication skills are expected.
- M.Sc. in Statistics, Biostatistics, Applied Mathematics, or related closely field with a minimum of 3 years of related industry and/or academic experience.
- Extensive experience in statistics (both Bayesian and non-Bayesian), statistical methodology, probabilistic programming, statistical machine learning, and data analysis.
- Advanced programming skills with fluency in at least Python and/or R, with experience using modern machine learning libraries (scikit-learn, caret, etc.).
- Strong communication and presentation skills with the ability to translate and communicate complex results to individuals of diverse backgrounds
- Team oriented and highly collaborative with strong organizational and communication skills
- Ability to address the requirements of the research team and develop new solutions, algorithms, and pipelines to facilitate biomedical discovery.
- Ph.D. and postdoctoral training in Statistics, Biostatistics, Applied Mathematics, or related closely field with a minimum of 3 years of related industry or academic experience.
- Extensive experience in structural causal modeling, and deep learning.
- Extensive experience in modern genomics analysis, including RNA-seq, single cell RNA-seq, DNA methylation, variant analysis, etc.
- Advanced programming skills with fluency in at least Python and R, with extensive experience using modern machine learning and deep learning libraries (TensorFlow, PyTorch, Edward, scikit-learn, caret, etc.).
- Up-to-date knowledge of the fast-moving AI/ML literature.
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