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<div style="margin: 0px;">Postdoctoral fellowship in data science for water quality, Stanford University</div>
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<div style="margin: 0px;">We are looking for qualified, creative and motivated postdoctoral scientists to lead research on the applications of machine learning to water quality. The postdoctoral fellow will be part of a vibrant new initiative for human-centered
artificial intelligence (HAI) at Stanford and will work with an interdisciplinary team of faculty with expertise in water quality, hydrology and data science. </div>
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<div style="margin: 0px;">Research description: To address the growing crisis in our water systems, the postdoctoral fellowship will focus on the integration of environmental data sets and physics-based models using machine learning. The work will address two
scales: California’s Central Valley and the continental U.S. and include several novel data streams, including geophysical imaging and new environmental sensors for water quality. Physics-based models will include integrated hydrologic models. The goal of
the project is to develop flexible and predictive models of water quality to safeguard our drinking water. </div>
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<div style="margin: 0px;">Applications require:</div>
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A PhD degree in science or engineering to be conferred prior to the start date</div>
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Extensive knowledge of computer science and or data science, particularly machine learning</div>
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Demonstrated programming skills</div>
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Ability to communicate effectively and collaborate across scientific domains</div>
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Some background in hydrology is desired, but this is not a strict requirement</div>
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<div style="margin: 0px;">Application Materials: Please provide a CV, contact information for three references, and a two-page research statement addressing the following points: (1) Describe two examples of how you have employed data science/machine learning
to address import questions; (2) What skill sets and abilities would you bring to this project? (3) What skills and abilities would you hope to gain from working on this project? Email applications to kmaher@stanford.edu. Closing date is June 30 and ideal
applicants will be available to start no later than September or October of 2019. This position is initially for one year and may be extended for up to three years depending on satisfactory progress and funding.</div>
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<div style="margin: 0px;">Additional information: Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation,
gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University’s research, teaching and clinical
missions.</div>
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<div>-- <br>
Kate Maher</div>
<div>Associate Professor</div>
<div>Department of Earth System Science</div>
<div>Stanford University</div>
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