Master Thesis - Decoding Occupancy: Classifying User Activity from Building Power Consumption with Machine Learning

At the Institute of Climate and Energy Systems Engineering (ICE-1) we focus on the development of models and algorithms for simulation and optimization of decentralized, integrated energy systems. Such systems are characterized by high shares of renewable energies and increasing sector coupling, which leads to high spatial and temporal variability of energy supply and demand as well as a high degree of interdependence of material and energy flows. Our research at the ICE institute aims to provide scalable and faster-than-real-time capable methods and tools that enable the energy-optimal, cost-efficient and safe design and operation of future energy system.

• Vertragsart: Vollzeit

Angebot

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with:

• Meaningful Tasks: Your thesis deals with a future-oriented, socially relevant topic with direct practical relevance in an international environment
• Practical relevance: With us, you will gain valuable practical experience alongside your studies and actively participate in interdisciplinary projects
• Scientific environment: You can expect excellent scientific equipment, modern technologies, and qualified support from experienced colleagues
• Personal responsibility: You organize your tasks independently-from preparation to implementation
• Work-life balance: We offer flexible working hours to help you balance your professional and personal life. You also have the option of flexible working (in terms of location), which is generally possible after consultation and in line with upcoming tasks and (on-site) appointments
• Flexibility: Flexible working hours make it easier for you to balance work and study
• Campus experience: Our research campus in the countryside creates ideal conditions for collegial exchange and sporting activities right on site. Our cafeteria offers a wide range of options-you can enjoy a relaxing lunch break with a lake view
• Fair remuneration: We will pay you a reasonable remuneration for your thesis In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits

Aufgaben

• Design a data pipeline to extract and preprocess activity-relevant features from monitored building power consumption data
• Develop a classification algorithm (e.g., based on Gaussian Processes or related probabilistic models) to infer user activity states from power signals
• Validate and benchmark your method against alternative classifiers on real building datasets
• Quantify and formalize uncertainty estimates to support reliable deployment in real-world building management systems

• Excellent university degree (Bachelor) in field of Data Science or a comparable field i.e. Electrical Engineering, Computer Science/Engineering, Physics
• Strong mathematical background
• Interest in energy systems, power grids and its components
• Excellent knowledge and experience in programming Python
• Excellent knowledge and experience in machine learning
• Experience with git is welcome
• Excellent ability for cooperative collaboration
• Very good command of written and spoken English with extensive vocabulary is required (at least B2 level according to the CEFR), ideally supported by a certificate confirming the language level
• Prior German knowledge is not strictly required

Pulled from the full job description

• Flexible schedule