Teaching Assistant Machine Learning - Berlin, Deutschland - Hertie School of Governance

Hertie School of Governance

Geprüftes Unternehmen

Berlin, Deutschland

vor 1 Woche

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

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 are looking for a

Teaching Assistant Machine Learning (gn)
part-time (7.5 hours/week), starting date 01 February 2024.

This course aims to deliver a practical introduction to the practice of machine learning.

The course covers standard topics in supervised and unsupervised learning, including the most common learning algorithms for regression, classification and clustering, but also touches on advanced topics in machine learning particularly important for public policy, such as uncertainty quantification.

The lectures associated with this course will be primarily based on Probabilistic Machine Learning:
An Introduction by Murphy along with assorted other topical readings.

Your tasks:

Prepare and teach two weekly 90minute labs, for 12 weeks, in person or online, depending on course needs;
Attend and support the weekly Machine Learning lectures;
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;
Preparation of course materials.

Your profile:

A solid background in machine learning (students at advanced undergraduate, Master‐ or PhD‐level), including experience with training neural networks using the PyTorch framework;
Excellent pedagogical skills (you should be able to explain the key concepts to highly motivated and hard‐working students with relatively little background in mathematics).

However, if you have recently successfully completed an advanced mathematics or machine learning course, and if you think you have necessary pedagogical skills, please do not hesitate to apply

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.

Please contact Jonida Popi, Coordinator Curricular Affairs, for further information.