A TA is required to support the convenor Prof. Vili Lehdonvirta in teaching Political Economy of Digital Markets, an 8-week option course for MSc Social Science of the Internet students in Weeks 1-8 of Hilary Term. 

The expected hours are up to 10 hours per week for 8 weeks (Weeks 1-8 of Hilary Term) up to a maximum of 80 hours in total, although some of these hours may be taken in Week 0 or 9 depending on convenor requirements. 

In this course we study the economic history of the Western Internet and learn fundamental theory from economic sociology and political economy to understand why the digital economy came to be dominated by centralized platforms and how it may in turn be shaping national economies and geopolitics. 

The TA is expected to read and briefly comment on students’ weekly one-page formative essays (for one half of the students, split with the convenor) and facilitate weekly group discussions (for one half of the students, split with the convenor). The TA will also assist the convenor with communications with the students between sessions. 

The prospective TA should have at least a basic familiarity with literature on the course’s reading list and the willingness to study the essential readings carefully before the class starts. The prospective TA should have experience in and/or the willingness to learn group discussion facilitation. 

Lectures for this course will take place Weeks 1-8, Mondays, 3-5pm. 

A TA is required to support the convenor Prof. Joss Wright in teaching Subversive Technologies, an 8-week option course for MSc Social Science of the Internet students in Weeks 1-8 of Hilary Term. 

The expected hours are up to 10 hours per week for 8 weeks (Weeks 1-8 of Hilary Term) up to a maximum of 80 hours in total, although some of these hours may be taken in Week 0 or 9 depending on convenor requirements. 

Subversive technologies provides an introduction to technologies related to security, privacy, and information control, and how these technologies intersect with society. The course aims to provide a contextual understanding of the realities of subversive technologies, and their capabilities, for students from a range of both technical and non-technical backgrounds. 

The TA is expected to attend lectures every week, to support the course convener in seminars and tutorials, as well as participating in discussions, and to be one point of contact for queries from students about administrative aspects of the course. 

The prospective TA should have experience with the history and context of subversive technologies, as well as some technical expertise. There are no strongly technical tasks for the TA to perform, but a knowledge of encryption, privacy technologies, internet censorship, and similar are a significant benefit in participating in seminars, tutorials, and discussions. 

Lectures for this course will take place Weeks 1-8, Fridays, 10.15am – 12.15pm.

A TA is required to support the convenors Prof. Ekaterina Hertog and Dr Gemma Newlands in teaching the eight-week methods option, Qualitative Interviewing and Data Analysis, which is offered to MSc Social Science of the Internet students in Weeks 1-8 of Hilary Term. 

The expected hours are up to 20 hours per week for 8 weeks up to a maximum of 160 hours in total, although some of these hours may need to be taken in Week 0 or 9 depending on convenor requirements.  This role could be offered to 1 TA at 20 hours per week or 2 TAs at 10 hours per week. 

The TA is expected to: 

(1) Be present at all eight lecture/seminar sessions (Thursdays, 1.30 – 3.30pm) and to facilitate seminar discussion and related activities in class;  

(2) Facilitate a weekly 1-hour drop-in sessions for students to help with assignments and general queries following the lectures (Thursdays, 3.30- 4.30pm);  

3) Assist in the provision of feedback on formative coursework (as required) and on CUREC forms completed by the students in relation to their course research projects.  

The prospective TA should have some previous experience of/engagement with digital interviewing and/or related qualitative research methods. 

A TA is sought to support the convenor Dr Mohsen Mosleh in the delivery of Advanced Statistics for Internet Research, an eight-week methods option offered to OII students on the MSc in Social Science of the Internet in Weeks 1-8 of Hilary Term. 

The expected hours are up to 10 hours per week for 10 weeks (including Weeks 0 and 9 of term) up to a maximum of 100 hours in total. 

This course uses covers multiple regression techniques (using R and RStudio) including the use of categorical variables, dummy variables, and interactions.  It will give students wider range of statistical techniques that they can apply in their own research, covering the interpretation of coefficients and odds ratios, measures of fit, supporting graphics, and diagnostics and corrective techniques for common problems.  

The prospective TA should be familiar with the topics covered in the course syllabus. 

The TA is expected to: 

(1) Be present at all eight class sessions (Thursdays, 09:30am – 11:30am); 

(2) Hold a weekly 1-hour drop-in surgery for students to help with the weekly assignments and general queries (Thursdays, 11.30am – 1230pm);  

(3) Assist in the provision of feedback on formative coursework (typically 6-8 assignments to mark per week with a 5-day turnaround) 

A TA is sought to support the convenor Dr Fabian Stephany in the delivery of Computational Methods for the Social Sciences, an eight-week methods option offered to OII students on the MSc in Social Science of the Internet in Weeks 1-8 of Hilary Term. 

The expected hours are up to 20 hours per week for 8 weeks up to a maximum of 160 hours in total although some of these hours may need to be taken in Week 0 or 9 depending on convenor requirements. This role could be offered to 1 TA at 20 hours per week or 2 TAs at 10 hours per week. 

The purpose of this course is to familiarize the student with collecting and wrangling structured and unstructured data from social websites and platforms, as well as simple visualisations, sentiment analysis, and statistical tests. 

The TA should have experience using Python, ideally to collect data using APIs and preprocess data in JSON/CSV format. 

The TA will participate in the classes (Tuesdays 11:30am – 1:30pm) and help students with their programming outside of class. 

The TA is expected to: 

(1) Be present at all eight class sessions and help students with the formative exercises in class;  

(2) Facilitate weekly 1-hour drop-in sessions for students to help with assignments and general queries on Wednesday afternoons;  

(3) Assist in the provision of feedback on formative coursework. 

(4) Help renewing the weekly Python scripts used in each class. 

A TA is required to support convenor Dr Robert Prey in teaching the eight-week methods option, Digital Ethnography which is offered to MSc Social Science of the Internet students in Weeks 1-8 of Hilary Term. 

The course explores the potential for use of ethnographic methods in the context of digital and online research. 

The expected hours are up to 16 hours per week for 10 weeks (including Weeks 0 and 9) up to a maximum of 160 hours in total. 

The TA is expected to: 

(1) Be present at all eight lecture/seminar sessions (Tuesdays 09:15am – 11.15am) and to facilitate seminar discussion and related activities in class; 

(2) Facilitate weekly 1-hour drop-in sessions for students (Wednesdays 4-5pm) to help with assignments and general queries; 

(3) Assist in the provision of feedback on coursework, including ethics clearance (CUREC) forms, as required. 

The prospective TA should have some previous experience of/ engagement with ethnographic methods, including (for example) embedded fieldwork, participation observation, interviewing and/or related qualitative research methods. 

A TA is sought to support the convenor Dr Fabian Stephany in the delivery of Research Design for Social Data Science, an 8-week core course for MSc Social Data Science students in Weeks 1-8 of Hilary Term. 

The expected hours are up to 10 hours per week for 8 weeks up to a maximum of 80 hours in total, although some of these hours may need to be taken in Week 0 or 9 depending on convenor requirements.   

The prospective TA should have experience in social data science research design, and will ideally have some experience of/engagement with a range of quantitative and qualitative methods. 

The TA is expected to: 

(1) Be present at all lectures (Tuesdays, 3-5pm) and to assist facilitating seminar discussion and related hands-on activities in class; 

(2) Facilitate weekly 1-hour drop-in sessions (Wednesdays, 2.45 – 3.45pm) for students to help with assignments and general queries; 

(3) Help students with general queries outside of class by email; 

(4) Assist in the provision of feedback on formative coursework.

A TA is required to support Prof. Carl-Benedikt Frey in teaching Frontiers of Social Data Science an 8-week core course for MSc Social Data Science students in Weeks 1-8 of Hilary Term. 

The expected hours are up to 6 hours per week for 8 weeks up to a maximum of 48 hours in total, although some of these hours may be taken in Week 0 or 9 depending on convenor requirements. 

This course will introduce students to the debates and practices surrounding the frontiers of social data science: with a particular focus on the economics of innovation. 

The TA is expected to: 

(1) Be present at all lectures (Tuesdays 9.15 – 11.15am) and to assist facilitating seminar discussion and related hands-on activities in class; 

(2) Help students with general queries outside of class by email; 

(3) Assist in the provision of feedback on coursework (such as the formative essay), as required; 

An ideal candidate has detailed knowledge of economics, and social science more broadly, to a level as covered in the course, both theoretical as well as practical. Preferences is given to DPhil students and post-docs working on economics and social science related topics and who ideally have previous tutoring experience. 

A TA is sought to support the convenor Dr Scott Hale in the delivery of Introduction to Natural Language Processing, an 8-week option course for MSc Social Data Science students in Weeks 1-8 of Hilary Term.  

The expected hours are up to 12 hours per week for 10 weeks (including Weeks 0 and 9) up to a maximum of 128 hours in total.  

A typical week might include verifying the instructions for formative assignments, assisting in the preparation of answer keys, answering student questions during a weekly Q&A period, reviewing work submitted by students, and other duties to be advised by the course convenor.  

Lectures for this course will take place Weeks 1-8 Tuesdays, 11:30am – 1:30pm with a 1-hour TA session Wednesdays, 1.30 – 2.30pm. 

A TA is required to support Dr Ana Valdivia in teaching Fairness Accountability and Transparency in Machine Learning. This 8-week option course is offered to OII students on the MSc in Social Data Science and MSc in Social Science of the Internet in Weeks 1-8 of Hilary Term.  

This course is designed to explore how algorithmic systems can contribute to social progress while also perpetuating or exacerbating oppression and social injustice. By drawing on critical data studies literature at the intersection of computer science and social science, the course aims to equip students with both computational and qualitative methods necessary to assess and address the impact of algorithmic systems in real-world contexts. Students are expected to engage critically, reflecting on their own experiences and the course materials to develop a nuanced understanding of the societal implications of algorithmic systems. 

The expected hours are up to 12 hours per week for 8 weeks up to a maximum of 96 hours in total, although some of these hours may need to be taken in Week 0 or 9 depending on convenor requirements.    

The prospective TA should be familiar with the topics covered in the course syllabus and range from a wide number of disciplines from philosophy, computer science, economics, political science, etc. 

The TA is expected to:  

(1) Be present at all lectures (Mondays, 11.30am – 1.30pm) and to assist facilitating seminar discussion and related hands-on activities in class;

(2) Hold a weekly 1-hour workshop (Fridays 3.30pm – 4.30pm) for students to help with formative exercises and general queries;   

(3) Provide feedback on Canvas on formative exercises and guide students towards the summative essay. 

A TA is sought to support convenor Dr Adam Mahdi in the delivery of Applied Machine Learning, an 8-week option course for MSc Social Data Science students in Weeks 1-8 of Hilary Term. 

The expected hours are up to 12 hours per week for 8 weeks up to a maximum of 96 hours in total, although some of these hours may need to be taken in Week 0 or 9 depending on convenor requirements. 

An ideal candidate has detailed knowledge of machine learning, to a level as covered in the course, both theoretical as well as practical. Preferences is given to DPhil students and post-docs working on machine learning related topics and who ideally have previous tutoring experience. 

Lectures for this course will take place Weeks 1-8 Thursdays, 09:30am – 11:30am with a 1-hour TA session Thursdays, 11.30am – 1230pm.