Research Assistant – “Influence of weather and climate on wireless data transmission with terahertz technology”
Technische Universität Berlin, Germany
Closing date: 21 June 2021
The tasks include the planning and implementation of the scientific work in the research project “Influence of weather and climate on wireless data transmission with terahertz technology” as part of the BMBF joint project AI-NET-PROTECT. The Chair of Climatology participates in planning, design and setting up of a test infrastructure for a hybrid network on the Campus Charlottenburg of TU Berlin. This hybrid network consists of wireless terahertz connections, so-called “virtual fibers”, which are embedded in a fiber optic infrastructure. For an intensive observation of atmospheric conditions within the test infrastructure, automatic weather stations will be set up on the campus as well as data from a weather radar system will be integrated. This experimental work is supplemented by microscale urban climate simulations in order to analyze the spatial variability of atmospheric conditions. The main subject of the investigations in network operation is the optimization and reliability of the “virtual fibers” taking into account changing weather conditions, in particular with regard to the spatial and temporal variability of precipitation as well as air temperature and atmospheric humidity.
The opportunity for pursuing a Ph.D. at TU Berlin is given.
TU Berlin is looking for a candidate who are highly motivated to pursue challenging scientific ideas and solve interdisciplinary problems. The successful candidate needs to satisfy the following requirements:
- Successfully completed academic university degree (Master, Diplom or equivalent) in the field of environmental science, information technology, computer science or comparable,
- Specific knowledge in the field of climatology and environmental meteorology with relevance for experimental atmospheric research,
- Knowledge of descriptive and exploratory statistics for the anaylsis of atmospheric variables,
- Knowledge and experience in programming of software solutions for the acquisition, processing, analysis and visualization of experimental data (Python, IDL, R),
- Experience in source-code management for software programming based on Git,
- Knowledge of Internet protocols (HTTP, FTP) and web-based technologies (API programming interfaces),
- Knowledge of scientific data standards (e.g. NetCDF, CF standard),
- Very good language and writing skills in English; good knowledge of German or the willingness to learn it.
In general, the ability to work in a structured and independent manner, determination, organizational and coordination skills, reliability, teamwork and communication skills are expected.