TEACHING ASSISTANTS for MSc SOCIAL DATA SCIENCE

We are looking for several TAs for courses and sections in the Master's program in Social

Data Science. The positions run from August 1st, 2023 – January 31st, 2024, with courses

organised in half-semester blocks: block 1 in week 36-42 and block 2 in week 43-50.

There are TA positions on the following courses and sections:

Social Data Science Base Camp (block 1 + 2):

Elementary Social Data Science (block 1):
Social Data Analysis (block 2):

SDS Coding Café (block 1 + 2), with potential for extension in the Spring 2024

Since Elementary Social Data Science and Social Data Analysis are taught in sequence, it

will be possible to get employed as TA on both.

Please state in the application which course and or section you wish to apply for and if

you are interested in a combined position.

Social Data Science Base Camp:
The course covers the Fall semester (14 weeks) with

4 hours of lectures and 6 hours of exercises/seminars per week. We are looking for TAs

to teach on the course seminars where students are introduced to the fundamentals of

programming, data collection, and data analysis in Python, covering topics such as

variables, data structures, functions, the social context of programming, APIs, scraping,

and basic regression and basic machine learning principles. In addition to the course

seminars, the TAs are expected to participate in regular coordination meetings with the

teaching team and assess student submissions throughout the semester.

Applicants for TA positions in Social Data Science Base Camp are required to have

experience working with the programming language Python, with programmatically

collecting online digital traces (e.g. using APIs or scraping), and knowledge of

regression. Knowledge of and experience with the Pandas library in Python is an

advantage, but not a requirement. Similarly, experience with teaching, in particular

teaching programming to beginners, is an advantage but not a requirement.

For further information, please contact the course coordinators Samantha Dawn Breslin

) and Gregory Eady ).

Elementary Social Data Science:
The course covers 4 hours of lectures and 6 hours of

teaching per week during block 1 (7 weeks). The teaching introduces students to a

typology of data and prominent research designs from the social sciences, discusses four

general approaches to data collection in Social Data Science, and reviews approaches to

sound research design and analysis. TAs' primary role will be to guide exercise sessions

building on the lecture content and, in cooperation with the course instructors, revise or

develop exercise session plans as necessary. In addition to the exercise sessions, the

TAs are expected to participate in regular coordination meetings with the teaching team

and might be asked to provide feedback on student projects throughout the course.

Applicants for TA positions in Elementary Social Data Science are required to have

experience conducting empirical social science research. Experience with handling

different types of data, conducting different forms of data collection, as well as with

various forms of social science research designs is an advantage, but not a requirement.

Similarly, teaching experience particularly at the university level is an advantage, but

not a requirement. For further information, please contact the course coordinator Lau

Lilleholt Harpviken ).

Social Data Analysis:
The course covers 4 hours of lectures and 6 hours of teaching

per week during block 2 (7 weeks). Teaching includes introductions to paradigmatic

theories, concepts, and methods for the social scientific study of human behavior, social

networks, and cultural ideas. In addition to the course seminars, the TAs are expected to

participate in the weekly lectures and coordination meetings.

Applicants for TA positions on Social Data Analysis are required to have experience

conducting empirical social science research. Experience with data collection, applying

novel data and research designs to classic social science problems, and open science

principles is an advantage, but not a requirement. For further information, please

contact Hjalmar Bang Carlsen ).

Coding Café:
The Coding Café runs on average four hours per week during the

semester and serves to support new students in the MSc in Social Data Science in their

introduction to the coding language Python. The Coding Café is a place where students

can come and ask coding questions and get extra help if needed. The students in the

program are introduced to fundamentals of programming, data collection, and data

analysis in Python, covering topics such as variables, data structures, functions, the

social context of programming, APIs, scraping, and basic regression and basic machine

learning principles. These are also the areas that the TA must be able to help with in the

Coding Café.

Applicants for the TA position are required to have experience working with the

programming language Python, with programmatically collecting online digital traces

(e.g. using APIs or scraping), and knowledge of regression. Knowledge of and experience

with the NumPy, Pandas, and matplotlib libraries in Python is a strong advantage, but

not a requirement. Similarly, experience with teaching, in particular teaching

programming to beginners, is an advantage but not a requirement. For further

information, please contact the Head of Studies Kristoffer Albris

).

Qualifications

The positions can be applied for by students who have at minimum completed the first 2

years of their bachelor's degree.

The teaching language is English, which means applicants are expected to be proficient

in English.

Salary and conditions of employment

The employment is made in accordance with the Collective Agreement between the

Danish Ministry of Finance and the National Union for Student Teachers (SUL)

The hourly salary is (per October 2023):

• Excl. preparation, 234,10 dkr per hour + vacation pay and pension.

Application procedure

After the expiry of the deadline for applications, the authorized recruitment manager

selects applicants for assessment on the advice of the Appointments Committee. All

applicants are then immediately notified whether their application has been passed for

assessment by an expert assessment committee. The selected applicants are notified of

the composition of the committee and each applicant has the opportunity to comment on

the part of the assessment that relates to his or her application. You can read about the

recruitment process at

Application

Apply by using the link at the bottom of the page. Please upload the following documents

in the electronic application form:

• Application
• Resumé
• Grade transcript from self-service at KUnet (in one joint file)
• If relevant, documentation for prior teaching experience and other relevant

academic qualifications (in one joint file)

Applications must be in English.

Please state in the application which course and or section you wish to apply for and if

you are interested in a combined position.

Remember to state your KU-email address in your application, as we will call in for

interviews via e-mail. If you are interested in a TA position, please send an electronic

application, resumé and relevant documentation via

The application deadline is

Please note that you can only upload one file in each category. If you have multiple

documents for the same category (e.g. diploma and grade transcripts), please collect all

the documents in one file (PDF).

Applications received after the application deadline will not be considered.

University of Copenhagen wants to reflect the surrounding society and encourages

anyone, regardless of personal background, to apply for the position.

---