Student Assistant Position (m/f/d, ≥40h/month)

University of Tuebingen

Germany

October 20, 2021

Description

08.10.2021

Student Assistant Position (m/f/d, ≥40h/month) Cluster of Excellence – Machine Learning for Science

Application deadline : 20.10.2021

The ML ⇌ Science Colaboratory at the Cluster of Excellence Machine Learning in Science has a

Student Assistant Position (m/f/d, ≥40h/month) on advancing ML ⇌ Science teaching material

available to be filled as soon as possible. The contract will be for the remainder of 2021.

The ML ⇌ Science Colaboratory runs introductory courses or workshops on machine learning for domain scientists in Tübingen who might benefit from ML methods in their own research.

Your tasks will be to assist us with curating existing teaching material, to develop interactive examples for practical sessions, and to support us with publishing educational content in various formats.

What matters most to us is that you share our enthusiasm for science communication and teaching. Ideally, you have some prior experience with machine learning, e.g. in previous courses or projects. The position is particularly suitable for students of the ML Master or adjacent degree programs, in which case you will be able to exploit synergies between your curriculum and the material we develop. Familiarity with Python, including a few common ML libraries (e.g. scikit-learn, pytorch) as well as Latex typesetting is essential, as is English proficiency. Any level of expertise with the Julia programming language is a plus, but not required.

Please send your application to Alexandra Gessner alexandra.gessnerspam prevention@uni-tuebingen.de. It should include (i) your CV, (ii) a recent transcript of records, and (iii) a piece of original work by yourself (could be a plot you are proud of, an excerpt from a report, or code that you have produced). Additionally, a short paragraph on your motivation and current situation of study (course plan) will be appreciated.

The deadline for application is October 20. Applications will be assessed on a rolling basis until the position is filled.

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