Position ID: | Duke-Department of Political Science-MIDSPOSTDOC [#21618] |
Position Title: | MIDS Postdoc |
Position Type: | Postdoctoral |
Position Location: | Durham, North Carolina 27708, United States [map] |
Subject Areas: | Political Science Data Science |
Appl Deadline: | 2022/06/13 11:59PM* finished (2022/04/13, finished 2022/12/17, listed until 2022/06/13) |
Position Description: |
Position
Description: Postdoctoral Associate: This position will start August 1, 2022, and will involve both a teaching component in Political Science and an educational component in the Masters in Interdisciplinary Data Science Program. The position will be for two years, with the possibility of renewal. The teaching component will entail developing
and teaching an introductory course in machine learning and text as data for
political science and decision science program students (at the mixed
undergraduate and graduate level).
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 projects between non-academic partners and Duke researchers who have interests and domain expertise aligned with partners’ goals. Capstones include research projects both with a variety of industrial partners, NGOs, and government bodies. 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 and also who are able to 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, and (c) helping train the MIDS students to become proficient and proactive researchers. There is overlap between the research and educational components of these positions. Fellows 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. Specific duties: The fellow will mentor teams of data science master’s students as they work on their year long Capstone projects. These projects pair student teams with external partners to generate insights and recommendations unique to the partner’s needs. Mentors must be able to regularly meet with the students to provide guidance, track progress, provide written feedback on papers, and resolve potential personal conflicts between team members and partners. Mentors will need to occasionally meet with project stakeholders to help students interpret and understand stakeholder needs. Mentors will report to the program director and will keep them updated with student progress. Good communication and project management skills are required. In addition, the fellow will develop and teach
an introductory course in the area of natural language processing and machine
learning for political science and decision science program students (a mix of
undergraduate and graduate students). 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.
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 Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values. |