Lead Teaching Assistant
vor 4 Wochen
The Hertie School in Berlin prepares exceptional students for leadership positions in government, business, and civil society. The school offers master’s programmes, executive education and doctoral programmes, distinguished by interdisciplinary and practice-oriented teaching, as well as outstanding research. Its extensive international network positions it as an ambassador of good governance, characterised by public debate and engagement. The school was founded in 2003 by the Hertie Foundation, which remains its major funder. The Hertie School is accredited by the state and the German Science Council.
We look to hire one **Teaching Assistant** (TA) for Prof. Dr. Lynn Kaack’s course **Deep Learning** in the Master of Data Science for Public Policy (MDS) of the Hertie School, for the Fall semester 2024 (01 August 2024 to 31 January 2025).
Your tasks:
- Prepare and teach two weekly 90-minute labs, for 12 weeks, in person or online, depending on course needs;
- Attend and support one of the weekly Deep Learning lecture;
- Student support, of which at least 60 weekly minutes should be regular office hours;
- Provide grading support and proctoring of exams and assignments for the instructor and assist with the development of the assignments themselves;
- For Lead TAs: Exam wrap-up and additional tasks of the Lead TA.
Your profile:
- A strong understanding of machine learning and especially deep learning (students at the Master‐ or PhD‐level, or equivalent practical experience).
- Experience with common deep learning frameworks such as TensorFlow or PyTorch.
- Excellent pedagogical skills (you should be able to explain the key concepts to highly motivated and hard‐working students with relatively little background in machine learning); an interest in developing teaching materials
We offer:
A stimulating international and diverse environment in multiple areas of social science, high-quality teaching and public policy. The Hertie School is a vibrant academic community that emphasizes excellence in research and teaching as well as an interdisciplinary perspective. Our school has been certified as a family friendly work environment in higher education and an equal opportunity employer. Severely disabled applicants are given preferential consideration in the event of equal qualification.
The total workload is 195 hours (average of 7.5 hours per week) over the 6-month contract (01 August 2024 to 31 January 2025) or 9 hours per week over a 5-month contract (1 September 2024 to 31 January 2025). The actual weekly workload can vary over the semester and will be agreed upon with the supervisor.
Please contact Lynn Kaack, Assistant Professor of Computer Science and Public Policy, for more questions about the position.
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