(100%) With your expertise, you will drive applied RD projects and service contracts to success. The Training Wind Energy Experts on Digitalisation (TWEED) Doctoral Network (DN) aims to train the next generation of excellent researchers equipped with a full set of technical and complementary skills to develop high impact careers in wind energy digitalisation. Co funded by the European Com mission through the Horizon Europe Marie Sklodowska Curie Doctoral Networks Programme, the TWEED network offers 12 Doctoral Candidates (DCs) positions to provide high level training in the new emerging research field of Wind Energy Data Science and Digitalisation. The goal of this DC project, titled Novel methods for a knowledge graph generation approach within TWEED''s Virtual Wind Farm Hub, is to investigate, design and implement a knowledge graph gen eration approach for the Virtual Wind Farm Hub within the TWEED project. The Virtual Wind Farm Hub will be an open platform to facilitate the exchange of datasets, research results and applications and allow domain experts and data scientists to prototype new services. Due to its status as a Swiss University of Applied Sciences, OST cannot matriculate or award PhD degrees. The PhD student will therefore be matriculated at ETH Zurich under Prof. Eleni Chatzi (Chair of Structural Mechanics and Monitoring), who will co supervise the thesis. The main supervi sor is Dr. Sarah Barber at OST (Institute of Energy Technology), and a further co superviser is Prof. Mitra Purandare at OST (Institute for Software). Required skills and qualifications: Completed Master''s degree (at the date of appointment) in a technical subject such as me chanical engineering, electrical engineering, or computer science, or equivalent Students currently in the final year of a Master''s degree are encouraged to apply but should note that if selected, they will be expected to start their PhD in the first quarter of 2025. Experience of and understanding of basic knowledge engineering concepts, including knowledge graphs, semantic web, ontologies and semantic artefacts Experience with programming languages such as Python, Javascript and Java Interest in and ability to work on interdisciplinary projects with a range of different people from outside your domain, especially at the interface between computer science and engi neering Excellent writing and communication skills in English Basic communication skills in German, or willingness to learn Ability to work in a team and independently Willingness to follow the mobility plan of the programme (conduct secondments in the country of the host institute) Fulfill the requirements for admission to the PhD program at the Department of Civil, Envi ronmental and Geomatic Engineering at ETH Zurich described here: https://baug.ethz.ch/en/doctorate/after 2022.html Optional: Experience with tools such as Spring, Node.js, Angular, React, Mongo DB, Elas ticsearch or TensorFlow Optional: Experience in wi