Description

The Division of Pediatric Gastroenterology, Hepatology, and Nutrition, a pioneer in research discovery, is seeking a highly motivated Data Scientist to build a state-of-the-art machine learning digestive diseases analytical platform. The position will support an exciting multicenter study with Mayo and Cleveland Clinic in Inflammatory Bowel Disease to derive a multimodal deep learning predictive model of treatment response. Experience with digital pathology to automate image classification and segmentation will be highly advantageous.

The candidate must be comfortable working as part of a team and requires effective communication with colleagues of various backgrounds, skill sets, and educational experiences. The multi-disciplinary nature of the program affords great opportunities for a candidate's growth and development.

Here's What You'll Get to Do:

• Apply state-of-the-art machine learning methods to clinical and molecular data
• Contribute to cutting-edge findings in biology and health
• Develop data processing and reporting pipelines to manage and maintain data quality and provenance
• Work in a casual work environment where learning and development are keys to success

Qualifications

EDUCATION/EXPERIENCE

Required:
??? Masters degree in related field. May require clinical license, certification or training
???5+ years of work experience in a related job discipline OR equivalent combination of education and experience

Preferred:

• PhD degree in biostatistics or computer sciences or related field AND 3 years' related experience
• Experience with computer vision, R and python, and Linux/Unix will be essential
• Understanding and experience with basic (e.g. random forest, SVMs) and advanced (e.g. deep learning, stochastic processes) machine learning methods is an asset
• Familiarity with statistical analysis of complex data including clinical data would be advantageous (insurance claims and/or electronic health records)
• Knowledge of biology is strongly encouraged
• Ability to function independently, yet collaboratively within a multidisciplinary team of various backgrounds, skill sets, and educational experience is required
• Ability to manage competing demands and deadlines with minimal supervision
• Excellent oral and written communication skills