Kompetenzzentrum Wasser Berlin (KWB) is a non-profit company for applied research and innovation founded in 2001 with over 35 employees. We develop research projects by crosslinking future topics like digitalization, resource efficiency, smart city and climate resilience with the traditional fields of the urban water cycle (www.kompetenz-wasser.de). In addition, KWB promotes the active transfer of knowledge to experts, municipal stakeholders, research partners, as well as to the interested public through public relations and the organization of events.
As part of an interdisciplinary research team within the “Urban Systems” group, you will work on research projects at the interface of hydroinformatics and engineering, contributing to climate adaptation and urban infrastructure resilience.
Your focus will be to support us to develop and test machine learning approaches for asset management in drinking water distribution system (DWDS). In particular, you will contribute to the uptake of our data-driven solution for asset management for sewer networks (SEMAplus) and help us to transfer it to the specifics of DWDS.
SEMAplus for DWDS will provide rapid and accurate information as well as a foundation for targeted short-term maintenance and long-term investment planning. To accomplish this, SEMAplus requires only a limited amount of pipe data (age, material, diameter, etc.), historic data on pipe failues, and, if available, data on other ageing-relevant environmental factors. The tool will help water utilities to save on resources, costs and time. SEMAplus for DWDS will also simplifies communication between decision-makers thanks to its easily understandable interactive dashboards.
Specific tasks include:
Nice to have