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The UW Department of Pediatrics is dedicated to improving the health of all children by educating physicians of the future, advancing research, advocating for children, and providing the nation's best pediatric clinical care. We are committed to building a diverse and inclusive faculty and staff.
The Division of Genetic Medicine is currently recruiting for a Research Scientist/Engineer 3 (RSE3) in the Chong Lab. Rare genetic disorders (also called rare diseases or Mendelian conditions) are individually rare, but collectively affect tens of millions of people in the U.S. alone and an estimated hundreds-of-millions worldwide. There are thought to be over ~5,500 different Mendelian conditions, each caused by mutations in one or more of ~3,800 genes. The increasing accessibility of genetic testing means that a genetic diagnosis and everything it entails—including a more accurate prognosis, better treatments, and accurate recurrence risk—could be in reach for millions of people. However, a major obstacle remains. Historically, Mendelian conditions have been described by subjectively grouping individuals who seem to share similar symptoms, and this approach is still used today. As a result, there is no objective, quantitative method applicable genome-wide for distinguishing between different Mendelian conditions. This poses a major challenge to the implementation of precision medicine and a barrier to improving the lives of the millions of people worldwide with a rare genetic condition.
This is a problem we are tackling at the Chong lab. In this position, you will research machine learning methods that integrate genetic and phenotypic data to assist in the diagnosis of and research into the causes of Mendelian conditions. You will have the freedom to develop new approaches and innovate on existing techniques to tackle an area rarely explored using machine learning by working with real-world data from tens of thousands of individuals. You will collaborate with clinical experts and researchers in human genetics and machine learning/data science to improve the precision and accuracy of patient diagnoses. Your work will advance our understanding of the fundamental biology of genetic disorders and will be critical to unlocking the power of new genetic tests and targeted therapies.
RESPONSIBILITIES: Job duties include but are not limited to: •Testing standard machine learning models (e.g., NMF, LDA, random forest, decision trees) •Feature engineering (different vectorization methods to accommodate domain-specific data) •Research, design, and create custom models to handle data with dependent relationships (e.g. ontologies) •Adapting or developing and validating simulated and real datasets for use in model evaluation •Enhancing data collection and extraction procedures for relevant data •Assessing models for bias due to correlated noise •Performing statistical analyses with traditional and machine learning methods •Contribute to preparation of research manuscripts, reports, presentations, reviews, and summaries •Actively participate and present summaries of work progress at group meetings •Other duties as assigned
REQUIREMENTS: •Master’s Degree in Computer Science, Data Science, Biostatistics, Computational Biology, Genetics or related field or equivalent work/education experience •Three or more years of relevant work experience •Basic understanding of genetics (e.g. rare/Mendelian vs complex traits, modes of inheritance) •Ability to communicate clearly in written and oral communications is essential •Must be comfortable working independently, taking the initiative to explore possible solutions, and doing both as part of a team •Expertise in common data science toolkits (e.g. Python, scikit-learn) •Excellence with machine learning techniques, particularly NMF, LDA, and decision trees •Flexibility to take on additional tasks as necessary to accomplish team goals
Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.
DESIRED EXPERIENCE • Familiarity with genetic mutation nomenclature/concepts and clinical finding terminology • Experience developing custom probabilistic models and/or experience applying deep learning methods to build context-aware recommender systems
Conditions of Employment: The employee will receive training in human subjects research and will be required to demonstrate knowledge and understanding of, and maintain confidentiality of patient privacy rights, employee information, Department of Pediatrics strategic plans and initiatives, financial information or other sensitive materials and information in printed, electronic or verbal form, which may jeopardize employee rights, the organization’s operations or privacy of patients. They will access and use the minimum necessary information to perform job responsibilities and duties and only for authorized purposes.
Application Process: The application process for UW positions may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Workforce Authorization, Cover Letter and/or others. Any assessments that you need to complete will appear on your screen as soon as you select “Apply to this position”. Once you begin an assessment, it must be completed at that time; if you do not complete the assessment you will be prompted to do so the next time you access your “My Jobs” page. If you select to take it later, it will appear on your "My Jobs" page to take when you are ready. Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.
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