Postdoctoral Associate: The Duke Masters in Interdisciplinary Data Science (MIDS) Program (mids.duke.edu) together with the Social Science Research Institute (SSRI; ssri.duke.edu) are seeking a postdoctoral fellow who (1) will make significant contributions to the research agenda of the Social Science Research Institute, and (2) will work to mentor, train, and educate MIDS students. The home institute for the fellow will be the Social Science Research Institute, which houses MIDS. The position will be for two years, with the possibility of renewal and will start August 1, 2022.

Research in SSRI relevant to this position will be conducted under the guidance of and in collaboration with Professor Nicholas Eubank. Specific research directions will be chosen via collaborative consensus and discussions with Professor Eubank. Research directions may end up being independent, in direct collaboration with Professor Eubank, or with collaborations across other departments/institutes at or beyond Duke. In general, collaborative research both within and beyond Duke will be encouraged. The research component of this role comes with the explicit goal of developing the postdoctoral associate’s research agenda.

Specific expectations related to research include: • A strong publication track-record. • Participation in relevant conferences and with the broader academic community.

Education in the MIDS Program culminates in a year-long intensive capstone project, in which teams of MIDS students make substantial contributions to real, complex problems proposed by non-academic stakeholders, such as a company, government agency, nonprofit, or internal Duke organization with support from at least one Duke researcher with expertise relevant to the problem being solved. A major goal for the capstones is to help transform the students from technical experts to proactive researchers who are capable of designing, refining, and executing research agendas as well as clearly communicate and disseminate their findings. The educational component of this position involves (a) facilitating and designing these capstone projects, (b) providing mentorship to MIDS students completing capstones, (c) helping train the MIDS students to become proficient and proactive researchers, and (d) assisting with conducting the capstone course.

Specific duties related to the Capstone component include: • Mentoring teams of data science master’s students as they work on their year-long Capstone projects. • Meeting with the students to provide guidance, track progress, provide written feedback on papers, and resolve conflicts between team members and partners. • Meeting occasionally with project stakeholders to help students interpret and understand stakeholder needs. • Reporting to the program director, keeping them updated with student progress. Good communication and project management skills are required. The Postdoctoral Associate will have opportunities to create capstone projects related to their interest and research. Fellows will also assist with existing capstone projects with political components. Past examples of Capstone projects include: systematically measuring the accessibility of polling places to college campuses for a voting rights group and analyzing how polling place access has changed over time; using NLP techniques to study political speech on social media; using LiDAR data to measure biomass for a carbon sequestration project; and analyzing the use of targeted Presidential campaign ads on Facebook. Fellows will also have an opportunity to recruit and interface with industrial partners, government agencies, NGOs, and more to help generate, refine, and resource problems and projects that are of direct value to these agencies. In addition, the Postdoctoral Associate will assist in selecting the incoming cohort of MIDS students by serving on the Admissions Committee during the spring semester, which entails reviewing applications. Finally, the Postdoctoral Associate will have the opportunity design and teach an elective course relevant to the individual’s expertise and the instructional needs of the MIDS department. This course will either be a 1.5 credit (half-credit) course taught by the individual or a co-taught 3 credit (full-credit) course jointly taught by the individual and a collaborator. The exact content of the course is subject to discussion, but substantive applications will be focused on political science and decision science research topics. The fellow will teach this course once per year. Required Skills/Knowledge/Abilities ● Proficiency in Python or R programming. ● Data processing skills including data cleaning (handling missing or corrupt data), analysis, and interpretation; managing and handling large datasets. ● Demonstrated comfort with applying both statistical inference and machine learning techniques. ● Experience with natural language processing, particularly text as data in social science applications. ● Ability to mentor and guide students in research projects. ● Ability to relate with stakeholders in recruiting projects and managing student-stakeholder relationships. ● Strong writing skills, as demonstrated by the ability to clearly describe statistical models and data-oriented research results. ● Polished verbal communication skills in presenting to both technical and non-technical audiences Desired Skills/Knowledge/Abilities ● Familiarity with data science collaboration tools (e.g. github, gitlab) ● Prior teaching experience in introductory courses in machine learning or NLP. ● Familiarity with a social science literature focused on either international relations or human decision-making.

Minimum Qualifications Education/Training: Work requires a Ph.D. degree in relevant technical field. Experience: Academic or professional experience with advanced data analysis and computer programming and experience mentoring or teaching required. Professional experience in applied data science is preferred.

How to Apply: Please Submit the following items to begin your application on Academic Jobs Online at https://academicjobsonline.org/ajo/jobs/: ● Curriculum Vitae ● Research statement ● Writing Sample ● Three reference letters (to be submitted online by the reference writers at this site

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