Research project "Interpretable Configurational Regression” looking for intern
Internship at a research project of the Department of Sociology in Lund. For students of the Department’s Master's programmes (internship courses SOCN20 and SOCN21).
The research project ‘Interpretable Configurational Regression’ is looking for an intern for the first half of the autumn semester of 2022
Internship, research projects at the Department of Sociology in Lund. For students of the Department’s Master’s programmes (internship courses SOCN20 and SOCN21).
Seeking an intern to work on a methodology-oriented project based on computational methods within the LU Department of Sociology. The intern’s tasks will be to work alongside an LU teacher/researcher (Chris Swader) in order to refine and continue to develop a machine learning method (’interpretable configurational regression’) for use especially by social scientists. Successful joint work might result in a co-authored publication and/or R package.
Essential qualifications include:
- knowledge of working with R and Rstudio
- knowledge of regression techniques
- basic understanding of interaction terms within regression
What tasks does the internship involve?
The intern’s tasks will include:
- programming in R
- refining the algorithm
- testing the algorithm
- literature review
- assisting with writing up the method and its use
September through October 2022.
The Department of Sociology in Lund.
How to apply
Send a letter of introduction (max of one A4 page), your CV, to christopher [dot] swader [at] soc [dot] lu [dot] se. Your letter should describe who you are, what you can contribute to the internship, and what you hope to gain from the internship.
Last application date
15 April, 2022.
Person responsible for the research project: Christopher Swader, christopher [dot] swader [at] soc [dot] lu [dot] se.
If you have general questions about internships at the Department of Sociology, you are welcome to contact Britt-Marie Johansson, britt-marie [dot] johansson [at] soc [dot] lu [dot] se.