Part -Time Research Assistant Required (WFU Student)

Professor Mark Curtis is looking for a skilled and driven individual to work as a part-time (up to 10 hours per
week) Research Assistant. The start date is subject to negotiation and may be as early as May 2019. Work
during the summer can be done remotely. The job will entail collaboration during all stages of empirical
research with Professor Curtis and co-authors at Duke University and the Federal Reserve Board. Current
projects are focused on areas of energy, taxes and the economics of entrepreneurship.
Job responsibilities span all stages of research, including collecting and analyzing data, creating presentations,
editing manuscripts and performing literature reviews. Typical research projects involve the collection of data
and analysis of energy policies, state-level taxes, occupational licensing and new firm formation. Independent
thinking, attention to detail, a thorough understanding of economics, and self-motivation are highly valued in
performing these functions.
Students must have taken Econometrics (Econ 209) and received a B+ or higher. Current Econ 209 students
will be considered but graduating Seniors are not eligible. Strong preference will be given to students who
have taken additional computer science and statistics courses but all graduate and undergraduate students in
Economics, Computer Science, Math, Statistics and Business are encouraged to apply; previous experience as
a research analyst is preferred; ability to collect data and write reports required.
The job is ideal for someone with an enthusiasm for data-driven research, and the ability and interest to learn
new skills and take initiative as a project develops. We welcome candidates with strong technical backgrounds
and an interest in energy and environmental issues.
How to Apply
• Email a cover letter, a current CV, and an unofficial transcript to Professor Curtis (
Your cover letter should describe your interest in the position; your familiarity with computer software
and programming languages (e.g., Stata, Excel, SAS, SQL, Matlab, ArcGIS, Tableau); prior relevant
experience and a Wake Forest Professor who can serve as a potential reference.
• Applications will be reviewed as they are received

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