Rsch Pro 6-Astrphys/Cosmology (Fortson)

The Zooniverse team in the School of Physics and Astronomy at The University of Minnesota has an opening for a Research Associate position focused on machine learning and data science applications in Astrophysics. 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 nearly 3 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 have recently received grant funding from NSF to support and improve on this infrastructure, including an "Incubator" that supports research teams in building their own custom front ends while using the Zooniverse back-end infrastructure to tackle at scale a wider range of tasks than can be built with current Zooniverse tooling. This is likely to include simple machine inference validation by humans in the loop, or more complex interactions between humans and AI as we seek to understand how to integrate e.g., Large Language Models into human-machine systems for scientific discovery. We seek individuals who are excited by the idea of building novel citizen science projects for their own work on data-intensive sub-fields of Astrophysics as well as working with other research teams to build a community of practice as they develop their own front-ends to optimize their project outcomes.

40% - Lead the Incubator effort including a Zooniverse researcher Community of Practice: Work with collaborators and research teams to support their custom front-end builds (termed Incubator Front Ends - IFEs), specifically in how to build well-designed citizen science projects that yield data useful to the research team while honoring volunteer engagement. Develop and provide resources (e.g., documentation, code examples or notebooks) for these teams to lower the barrier for their use of human-in-the-loop strategies with Zooniverse volunteers. Build and maintain a GitHub repository that will serve as the core touchpoint for developing a community of practice (CoP) primarily for researchers wishing to build IFEs, but useful for a range of Zooniverse research teams. With assistance from PIs and collaborators, organize, lead and expand the CoP including holding regular meetings, and documenting and supporting needs of the community. Assist PIs, collaborators and the CoP in identifying and using open data and code sharing practices.

40% - Astrophysics Research: Carry out a research program exploiting astrophysics-related data sets developed by the research associate through Zooniverse and/or their own IFEs. Communicate results via academic publication in appropriate journals. Mentor graduate and undergraduate students who are tasked with developing, implementing and analyzing some aspects of the program.

20% - Communication, dissemination, service and professional development: Take the initiative to keep all project stakeholders informed of progress or concerns. Collaborate with key partners to assist the wider grant effort particularly with planning, documentation, and dissemination of products at workshops. Contribute as appropriate to project reports to the granting agency. Take a leadership role in wider Zooniverse team meetings and discussions on strategy and development. Represent the Zooniverse team at meetings and conferences as required. Contribute to Zooniverse service tasks such as general project review, and participation in relevant working groups. Maintain professional development, trying out and becoming familiar with new technologies through individual initiative as well as through drawing on collaboration and support from team members.

Other duties as assigned

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 with substantial research and publication record. 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. In addition, applicants must have demonstrated leadership experience in organizing or coordinating groups towards a common objective (e.g., run a working group, coordinated a journal club, organized regular coding sprints or workshops). 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 some web development skills in a research context in either academia or industry as well as demonstrated familiarity with machine learning in the context of research with human-computer systems; a demonstrated interest in citizen science; the ability to manage multiple projects; excellent organizational, presentation and writing skills; and demonstrated self-motivation and creativity. While based in Minneapolis, the successful applicant will be expected to travel for collaboration purposes to Chicago and Oxford, UK.

School of Physics and Astronomy: https://cse.umn.edu/physics

Pay Range: $65,000 - $100,000; depending on education/qualifications/experience

Time Appointment: 100% appointment

Position Type: Faculty and P&A Staff

Please visit the Office of Human Resources website for more information regarding benefit eligibility.

The University offers a comprehensive benefits package that includes:

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program
• Low-cost medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and employer-paid life insurance
• Employee wellbeing program
• Excellent retirement plans with employer contribution
• Public Service Loan Forgiveness (PSLF) opportunity
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost
• Employee Transit Pass with free or reduced rates in the Twin Cities metro area

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will have the opportunity to complete an online application for the position and attach a cover letter and resume.

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

Deadline for applications is January 23, 2026.

In your application materials, please include:

1. A cover letter explaining why you are interested in the position and why you believe you are qualified,
2. Curriculum vitae including recent publications,
3. A 1-2 page research experience statement highlighting any machine learning work you have done, and
4. The names and full contact information for 3 references who have been asked to submit letters by January 23, 2026.

This position will remain open until filled.

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-8647.

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

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