Student assistant (40 hours per month)

• Supervision of small-group exercises designed to reinforce and apply the material covered in lectures (weekly 90min) of the module #51049 – Applied Machine Learning (AML) (20%), in particular supervision during the independent work phase (20%)
• Advising students on object-oriented Python programming and machine learning methods as part of a student
  consultation hour (20%)
• Creation of additional didactic teaching material for small-group exercises, especially Python scripts and Jupyter notebooks (20%)
• Assistance with the preparation and follow-up of small-group training materials (20%)
• Participation in work and debriefing meetings with Prof Stender and other tutors (20%)

MUST:

• Very good and demonstrable knowledge of the Python programming language and object-oriented programming
• Detailed knowledge of the programme libraries Numpy, Scikit-Learn, Matplotlib, Jupyter-Notebook
• Sound knowledge in all of the following subject areas: Linear and logistic regression, decision trees, ensemble methods, clustering methods, neural networks, error backpropagation
• Experience with Moodle-based learning platforms
• Very good written and spoken English skills

CAN:

• Experience in university teaching
• Proactive communication and reliability

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