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Offer 14 out of 149 from 13/05/25, 13:33

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Tech­ni­sche Uni­ver­si­tät Ber­lin - Fakultät V: Verkehrs- und Maschinensysteme - Institut für Maschinenkonstruktion und Systemtechnik - FG Cyber-Physical Systems in Mechanical Engineering

Technische Universität Berlin offers an open position:

Student assistant (40 hours per month)

Working field:

  • Supervision of the exercises (weekly 90min) of the module 51077 – Applied Deep Learning (ADL) (20%), in particular supervision during the independent work phase (20%)
  • Advising students on object-oriented Python programming and deep learning methods as part of a student consultation hour (20%)
  • Creation of additional didactic teaching material for exercises, especially Python scripts and Jupyter notebooks (20%)
  • Technical-organisational and didactic preparation and follow-up of exercise teaching content (20%)
  • Participation in work and debriefing meetings with Prof Stender and other tutors (20%)

Requirements:

MUST:

  • Very good and demonstrable knowledge of the Python programming language and object-oriented programming
  • Detailed knowledge of the programme libraries Keras, Tensorflow, Numpy, Matplotlib, Jupyter-Notebook
  • In-depth knowledge of all of the following topics: Forward neural networks, error feedback, recurrent NN, convolutional NN, object detection, image segmentation, reinforcement learning, transformers
  • Experience with Moodle-based learning platforms
  • Very good written and spoken English skills

CAN:

  • Experience in university teaching
  • Willingness and readiness to further develop high-quality teaching

How to apply:

Party responsible for specialist area / point of contact for job posting: Prof. Dr.-Ing. Merten Stender
Period of employment: immediately for 2 years
Apply to: merten.stender@tu-berlin.de

Please submit your written application including cover letter, your CV, certificate of enrollment, and where applicable, current transcript of records, with the reference number to the place of employment indicated above.
In the interest of promoting equality opportunities for men and women, applications from women with suitable qualifications are particularly encouraged.