The Genuity  Artificial Intelligence Research Institute (GAIRI) at Genuity Science is seeking a highly motivated leader of our Computer Vision function to help pioneer the use of generative and supervised AI/ML in the biomedical sciences. The candidate will manage a small team and work on data generated from clinical pipelines and use AI/ML, computer vision, and other statistical genomics approaches to analyze various large-scale image and omics data sets 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.

Essential Qualifications

  • M.Sc. in Engineering, Computational Statistics, Computer Science, Data Science, or related field with a minimum of 4-years of related industry and/or academic experience
  • Minimum of 2 years of industry and/or academic research laboratory management experience
  • Experience in computer vision, CNNs, machine learning, deep learning, statistical methodology, predictive modeling and algorithm development
  •  Advanced programming skills with fluency in at least Python and/or R, with extensive experience using modern machine learning and deep learning libraries (TensorFlow, PyTorch, openCV, Edward, sklearn, caret, etc.)
  • Proven ability to design and code production grade machine AI/ML applications, along with a strong ability to visualize ‘big data’
  • Ability to work on high-performance computing system and manage cloud computing environments (e.g. AWS) with experience working with GPUs
  • Strong communication and presentation skills with the ability to translate and communicate results to individuals of diverse backgrounds

Preferred Qualifications:

  • Ph.D. and postdoctoral training in Computer Vision, Computer Graphics, Image Processing, Applied Mathematics, Engineering, Computational Statistics, or related field
  • Understanding of modern genomics analysis including RNA-seq, single cell RNA-seq, DNA methylation, variant analysis, etc.
  • Working knowledge of biology (oncology, immunology, autoimmunity, etc.) and experience in drug target identification
  • Up-to-date knowledge of the fast-moving AI/ML literature

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