Society for Learning Analytics Research
Postdoctoral Fellowship
Society for Learning Analytics Research, Washington, District of Columbia, us, 20022
Postdoctoral Fellowship
Harvard University: Graduate School of Education
The Strategic Data Project (SDP), an initiative of the Center for Education Policy Research at Harvard University, is offering a one-year research fellowship at the postdoctoral level starting in the summer of 2021. The fellow will work at a US Federal Agency in Washington, DC and engage in research projects related to the department’s focus.
Federal research leaders are working to realize the potential of previously untapped data collected across multiple federal agencies. To carry out the work of bringing together new data sets and tools and publishing novel insights, SDP will host the inaugural cohort of post-doctoral data fellows to work with federally collected education data and to connect those data across departments to generate new insights about the health, well-being, and achievement of students.
The postdoctoral fellow will have the opportunity to work with Harvard faculty advisors focused on education policy research, such as Tom Kane and Chris Avery. Additionally, they will engage in ongoing research projects and will participate in the design of new studies utilizing federal data sets at a summer summit of faculty, fellows, and researchers that kicks off the fellowship program. Finally, fellows will have the opportunity to access Strategic Data Project training opportunities as desired.
Generally, fellows should expect to spend about 75% of their time working on ongoing research projects at a US Federal Agency, while dividing the other 25% between building new collaborations and developing independent research projects.
Qualifications Applicants must have completed their PhD in a relevant social science discipline prior to August 31, 2021 and have academic research experience in public policy, economics, education, quantitative methodology, or other similar fields. Applicants must have experience with large administrative data sets, sampling methods and primary data collection processes; knowledge of education policy issues; experience with data processing, archiving, analysis and report writing, including statistical analysis; experience with major social science databases and statistical software packages; excellent communication skills, both oral and written; attention to detail; the ability to multi-task and prioritize efforts across simultaneous projects. Applicants must be citizens or permanent residents of the United States.
The skills needed for each project will vary and Fellows will match to projects based on the skills they bring. Some of the high priority skills include: quantitative research; experience modeling for predictive analytics and program evaluation; experience with R and/or Python, and natural language processing; process/clickstream data analysis; and machine learning (e.g. unsupervised learning, predictive analysis, automated feature extraction). Candidates with data science experience are preferred.
Application Instructions Applicants should submit the following materials no later than May 31, 2021 at 11:59 pm EDT. We will begin reviewing applications on May 16, 2021.
Applications must include:
Curriculum Vitae
Statement of interest (2-3 pages)
Unofficial copy of academic transcript(s)
Two samples of writing, if not published, then of publishable quality (job market paper or recent publication authored / lead-authored by the applicant)
3 confidential letters of recommendation sent directly from the references to
sdprecruitment@gse.harvard.edu
#J-18808-Ljbffr
Harvard University: Graduate School of Education
The Strategic Data Project (SDP), an initiative of the Center for Education Policy Research at Harvard University, is offering a one-year research fellowship at the postdoctoral level starting in the summer of 2021. The fellow will work at a US Federal Agency in Washington, DC and engage in research projects related to the department’s focus.
Federal research leaders are working to realize the potential of previously untapped data collected across multiple federal agencies. To carry out the work of bringing together new data sets and tools and publishing novel insights, SDP will host the inaugural cohort of post-doctoral data fellows to work with federally collected education data and to connect those data across departments to generate new insights about the health, well-being, and achievement of students.
The postdoctoral fellow will have the opportunity to work with Harvard faculty advisors focused on education policy research, such as Tom Kane and Chris Avery. Additionally, they will engage in ongoing research projects and will participate in the design of new studies utilizing federal data sets at a summer summit of faculty, fellows, and researchers that kicks off the fellowship program. Finally, fellows will have the opportunity to access Strategic Data Project training opportunities as desired.
Generally, fellows should expect to spend about 75% of their time working on ongoing research projects at a US Federal Agency, while dividing the other 25% between building new collaborations and developing independent research projects.
Qualifications Applicants must have completed their PhD in a relevant social science discipline prior to August 31, 2021 and have academic research experience in public policy, economics, education, quantitative methodology, or other similar fields. Applicants must have experience with large administrative data sets, sampling methods and primary data collection processes; knowledge of education policy issues; experience with data processing, archiving, analysis and report writing, including statistical analysis; experience with major social science databases and statistical software packages; excellent communication skills, both oral and written; attention to detail; the ability to multi-task and prioritize efforts across simultaneous projects. Applicants must be citizens or permanent residents of the United States.
The skills needed for each project will vary and Fellows will match to projects based on the skills they bring. Some of the high priority skills include: quantitative research; experience modeling for predictive analytics and program evaluation; experience with R and/or Python, and natural language processing; process/clickstream data analysis; and machine learning (e.g. unsupervised learning, predictive analysis, automated feature extraction). Candidates with data science experience are preferred.
Application Instructions Applicants should submit the following materials no later than May 31, 2021 at 11:59 pm EDT. We will begin reviewing applications on May 16, 2021.
Applications must include:
Curriculum Vitae
Statement of interest (2-3 pages)
Unofficial copy of academic transcript(s)
Two samples of writing, if not published, then of publishable quality (job market paper or recent publication authored / lead-authored by the applicant)
3 confidential letters of recommendation sent directly from the references to
sdprecruitment@gse.harvard.edu
#J-18808-Ljbffr