Student assistant (40 hours per month)

Supporting activities for an internal TU research funding (Forschungsanschub):

• Processing and preparation of mobility and geospatial base data (25%)
• Implementation of Python scripts (25%)
• Training machine learning models (10%)
• Implementation of deep learning models (10%)
• Conducting scientific research tasks (20%)
• Editorial processing of scientific texts (10%)

• Strong expertise in processing and analyzing mobility and geospatial base data
• Proficiency in relevant GIS software (e.g., QGIS, ArcGIS Pro)
• Solid understanding of common geodata standards (e.g., OGC standards, INSPIRE)
• Strong programming skills in Python software development
• Experience with version control (e.g., Git, GitHub, or GitLab)
• Experience in machine learning, particularly neural networks
• Proficiency in Linux and the command line
• Knowledge in geodesy and geoinformation science
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills

Party responsible for specialist area / point of contact for job posting: Prof. Dr. Martin Kada
Period of employment: immediately for 2 years
Apply to: pia.daute@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.