Student Assistant: Future Data Infrastructure of Smart Grids 10%-30%

pAs part of Grid2050 and NCCR Automation, we are building a high-performance, secure, and fault-tolerant data infrastructure to power cutting-edge energy research. Grid2050 connects real-world electricity grid measurements, smart meter data, and actuator control into a single ecosystem for experimentation at scale. /p pbProject background /b /p pThe future smart grid features the widespread integration of distributed energy resources, introducing new challenges to infrastructure in areas such as automatic control, data management, and communication. The Internet of Things, big data technologies, and operational technology must be reliably and securely integrated to ensure smart grid operations. /p pWe are seeking a reliable and highly motivated student assistant to support our research.

In this role, you will design and develop data infrastructure to tackle real-world challenges in smart grid research, ensuring our infrastructure meets requirements in the future-such as scalability under load, resilience to failure, and adaptability to change. /p pThe starting date is flexible but an early start is preferred. /p h3Job description /h3 ul liInfrastructure Development: Work in containerd environments, ensure the security, availability, scalability and accountability of our server. /li liCommunication Pipeline: Enhance and extend data and command transmission intrastructure between ETH, utilities, and energy management systems-ensuring they're reliable (think "backpressure handling" and "exactly-once" semantics) and maintainable. /li liDatabases: Work with time-series databse designed for high-volume ingestion and low-latency queries, and make sure they are scalable and

realible under extreme scenarios. /li liReliability Recovery: Implement replication, backup, and disaster recovery strategies-making sure the system survives faults without losing data. /li liFront-end Development: Build visualization dashboards (Grafana) and remote experimentation APIs to give researchers live insight into grid behavior and improve user experiences on our platform. /li /ul h3Profile /h3 ul liYou are an ETH student enrolled in Computer Science, Electrical Engineering, Power Engineering, or related fields. /li liYou are passionate about data engineering, systems development, and energy-related topics. /li liYou are fluent in English.

German is a plus but not mandatory. /li liYou are available to work approximately 8 - 15 hours per week (i.e. one or two days per week). /li liYou have strong expertise in Git, Python, and Linux development environments. /li liIdeally, you have worked with one or some of the following fields: RabbitMQ, Grafana, SQL, Docker, and front-end development. /li liYou pay strong attention to details, and you work responsibly. /li /ul h3We offer /h3 ul liHands-on experience with real-world data infrasturcture, and distributed system design. /li liWorking alongside leading academics, industry partners, and a collaborative research community.

Rare chance to see theory play out on a real part of our critical infrastructure. /li liFlexible working conditions, state-of-the-art facilities, and remuneration according to ETH student assistant salary guidelines Stundenlohn - Staffnet | ETH Zürich. /li /ul h3We value diversity and sustainability /h3 pIn line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us - we are consistently working towards a climate-neutral future. /p h3Curious?

So are we. /h3 pQuestions regarding the position should be directed to Hanshuo Wu ( ) (no applications). /p pFurther information about the research group can be found on our Website. /p pWe would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence. /p