Are you passionate about programming and anything related to digital technology? Or more specifically in machine learning, natural language processing and network analysis? Would you like to help teach students the foundations and advanced applications of these digital skills? We are looking for new additions to our teams of Teaching Assistants and you may just be one of them!In September 2022, a brand new Bachelor's programme at the UvA welcomed its first students: Computational Social Science. This interdisciplinary programme is a collaboration between the faculties of Social and Behavioural Sciences (FMG), Science (FNWI) and Humanities (FGw).
Students will learn how to analyse 'real world' data on complex societal issues such as climate change, global health and digital surveillance to identify opportunities for (behavioural) change and to design evidence-based intervention strategies. They will programme hands-on tools that support sustainable digital innovation and contribute to making the world a better place!
Computational Social Science is an English-taught programme with a unique curriculum that is solely made up of project driven, semester-long courses of 30 EC. More information can be found
here.
What are you going to do?Digital Expertise (DE) plays an essential role in all teaching and learning within Computational Social Science. There will be guest lectures, practical sessions, and components of student group projects devoted to DE content. As a Teaching Assistant for first year students and or second year students, you will mostly be:
- supervising practical sessions;
- answering digital expertise-related questions from students;
- grading weekly individual DE assignments.
Within our programme, each semester-long course has a fixed weekly schedule for all lectures, workshops, practical sessions and deadlines.
- Practical sessions in DE for first year students in (Python) programming are mostly scheduled on Monday (afternoons), Wednesday and Friday (mornings);
- Practical sessions in DE for second year students in ML, NLP and network analysis will mostly take place on Tuesdays and Thursdays.
You will be assigned to a group of students for the duration of 20 weeks (i.e. one semester). Each group will consist of approximately 20 students.