Astronomy and Space Science, Computer Science: Programming, Physics: Astrophysics
The Zooniverse team within University of Minnesota’s School of Physics & Astronomy is seeking a Researcher 6 (Research Associate) in Data Science for Machine Learning and Citizen Science for the Zooniverse.org (github.com/zooniverse) platform.
The Zooniverse team in the School of Physics and Astronomy at The University of Minnesota has openings for three Research Associate positions; two focused on machine learning and data science applications in Astrophysics; one focused on machine learning and data science applications in Medical Imaging and Humanities. This job description is for the lead Astrophysics position. We seek a research associate with strong experience in data science and machine learning to further develop the world’s largest platform for citizen science. Zooniverse uses the combined input from over 2 million volunteer classifiers to provide labeling and other tasks across hundreds of research projects in a variety of domains. Under the onslaught of ever-larger amounts of data and to take advantage of improvements in machine algorithms, the Zooniverse team has built and implemented infrastructure to enable novel approaches that optimally combine human and machine classifiers. We seek individuals who are excited by the idea of using this new infrastructure on data-intensive sub-fields of Astrophysics with the goal of most efficiently classifying “known-knowns” while at the same time enabling the serendipitous discovery of completely new classes of objects in a given astrophysical dataset.
The research associate will be supervised by Lucy Fortson, faculty member in Physics and Astronomy, co-founder of Zooniverse and director of the Zooniverse effort at UMN. The UMN Zooniverse effort comprises science team members across multiple Zooniverse projects including many in Astrophysics, several data science research associates and students working in astronomy, ecology, medical imaging and digital humanities, and a dedicated Zooniverse web developer. The successful applicant would work closely with Zooniverse team members at the Adler Planetarium in Chicago and the University of Oxford, UK who are guiding and developing the Zooniverse platform infrastructure to combine human and machine classifiers; there is a budget for several collaborative visits to these locations for this project. Additionally, the research associate would be expected to work with and directly mentor graduate students from the UMN Data Science Masters program as well as undergraduates from a range of domains with assistance from several faculty in Computer Science and the Informatics Institute at UMN who are engaged in Zooniverse projects. The Zooniverse uses the best technology available to provide cutting-edge tools to scientists using our platform; we expect the results produced by the research associates to be adopted by the team and deployed in production. The position is grant-funded for two years with the possibility of continued funding if further grants are successful.
Required: Applicant must hold a Ph.D. in a relevant subject (e.g. in a data-intensive field such as Physics or Astronomy) or in computer science. It is essential that the applicant have demonstrated experience with a set of tools appropriate for working with large-scale data science including application of machine learning. A strong publication record in relevant academic field(s) is also required as is the ability to mentor students and work in a diverse, distributed team in an interdisciplinary manner with an ability to direct one’s own research.
Preferred: Preference will be given to applicants who have experience implementing machine-learning algorithms in a research context in either academia or industry as well as demonstrated familiarity with classifier combination problems or with research into human-computer systems; a demonstrated interest in citizen science; the ability to manage multiple projects; experience in managing working groups or small teams; excellent organizational, presentation and writing skills; and demonstrated self-motivation and creativity. While based in Minneapolis, the successful applicant will be expected to travel to Chicago and Oxford, UK.
We only accept on-line applications (see url above). The position is open effective immediately. Applications will be accepted until the position is filled. Apply here: https://hr.myu.umn.edu/jobs/ext/338067
a cover letter explaining why you are interested in the position and why you believe you are qualified,
curriculum vitae including recent publications,
a 1-2 page research experience statement highlighting any machine learning work you have done,
the names and complete contact information for three references.
Additionally, have three letters of reference sent preferably via email to:
Professor Lucy Fortson School of Physics and Astronomy University of Minnesota 116 Church Street SE Minneapolis MN 55455
The University of Minnesota is committed to the policy that all persons shall have equal access to its programs, facilities, and employment without regard to race, color, creed, religion, national origin, sex, age, marital status, disability, public assistance status, veteran status, or sexual orientation.
Internal Number: 338067
About University of Minnesota
See more information about the School of Physics and Astronomy at the University of Minnesota at www.physics.umn.edu
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