Research - Laboratory/Non-Laboratory, Staff/Administrative
This position is being re-posted. If you have already submitted your application, you do not need to submit it again, as it has been received.
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The Department of Bioengineering is recruiting a Data Scientist (Research Scientist 3) with expertise in biostatistics to develop new diagnostic algorithms based on Bayesian models.
Our work is focused on enabling at-home self-testing for influenza and other infectious diseases of global importance (e.g., TB, HIV, malaria, STIs). This position is focused on extracting meaningful information from data and ensuring high quality data bases. COVID-19 has shown the need to rapidly diagnose infectious diseases. Our group is developing ways to identify individuals who are likely to be infected using available information from disease mapping, known risk factors, and symptoms or other physiological indicators.
Do you have strong analytical and computational skills, a can-do attitude, and interest in working on a cutting-edge concept-driven problem in health? We are seeking a Data Scientist to develop models and computational tools to assess the probability that individuals are infected with COVID-19, influenza, and other respiratory diseases as part of the Seattle Flu Study. These tools could be applied to identify where to test, who to test, and what test should be used, and we aim to identify partners to pilot this selective testing approach, e.g., via a phone-based app. Our group is also engaged with the Bill & Melinda Gates Foundation to collaboratively develop similar tools for tuberculosis and other diseases of global health importance.
RESPONSIBILITIES •The position will perform data analysis and extraction, manage data population goals, and collaborate with others to accomplish these goals. •The technical work will include developing deep knowledge of prior work in flu testing and clinical prediction rules, developing models of rapid flu test performance, and testing models on existing or prospective data. •Develop and implement a set of techniques to transform raw data into meaningful data. Apply data mining, data modeling to extract and analyze information. Innovative extraction of meaningful data from various data sets. •Develop conceptual approaches based on a foundation of biostatistics. •Other duties: Report results internally within the large Seattle Flu Study collaboration, work with internal and external collaborators, and publish results in peer-reviewed journals with assistance from faculty where needed.
MINIMUM REQUIREMENTS •Bachelor’s Degree in biostatistics, mathematics, computer science or related discipline •Three to five years of experience in related field. •Demonstrated experience with the following: oMultivariate analysis, stochastic modeling, Bayes’ statistics oDeveloping statistical and machine learning models oData visualization capability •Expertise in biostatistics including predictive model development (e.g., logistic regression, LASSO, other machine learning methods) and Bayesian statistics. •Demonstrated strong skills in writing and oral communication.
Equivalent education and/or experience may substitute for minimum requirements.
DESIRED REQUIREMENTS •Master’s Degree in biostatistics, mathematics, computer science or related discipline. •Professional experience working in the field of infectious disease diagnostics or related area. •Mobile application development. •Demonstrated record of publication.
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