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Master Thesis - Hybrid ML + LLM-based Fault Detection and Explainability for Smart Building IoT Systems

Forschungszentrum Jülich GmbH -
Jülich

Direkt bewerben

Details zur Stelle

Teilzeit

Leistungen

Flexible Arbeitszeiten

Qualifikationen

Informatik
Englisch
Master
Systems Engineering
Künstliche Intelligenz
Python

Vollständige Stellenbeschreibung

Master Thesis - Hybrid ML + LLM-based Fault Detection and Explainability for Smart Building IoT Systems

At the Institute of Climate and Energy Systems - Energy Systems Engineering (ICE-1), we develop advanced models and algorithms for the simulation and optimization of integrated multi-energy systems. Within the Living Lab Energy Campus (LLEC) project, large office buildings are equipped with many IoT devices, typically 5-10 devices per office room. These devices transmit real-time data such as the opening state of windows, doors as well as room air quality and luminance measurements to a cloud infrastructure. Additionally, through a user-facing energy dashboard with a desk booking system, building occupants can interact bidirectionally with the building systems. These occupant-building interactions are the basis for several avenues of research including the intelligent operation of heating and shading systems. As part of our team, you will contribute to the smooth and reliable operation of the building systems through implementation of online fault detection and diagnosis, and subsequent communication of the results to real users in a real-world setting.

Vertragsart: Teilzeit

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: Hands-on as well as theoretical work in a Living Lab setup with existing tools and supporting frameworks
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
Onboarding & teamwork: You can look forward to working in a dedicated, international, and collegial team. It is important to us that you quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide
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
Health & well-being: Your health is important to us. You can look forward to a comprehensive company health management programme with a wide range of options, including a beach volleyball court, running groups, yoga classes and much more. In addition, our company medical service and an experienced social counselling team are available to assist you on site
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

Installation and configuration of available occupancy detection sensors (e.g. PIR sensors, PQI meters, infrared camera, etc.)
Setup of suitable experimental plan for testing the occupancy estimation approaches
Analysis of characteristics of the various approaches in terms of ease of setup, cost, data quality, suitability for different end-uses, etc.
Analysis of combinations of approaches in terms of detection accuracy and reliability

Profil

Ongoing masters degree studies in computer science, data science, engineering, machine-learning, or other closely related field
Good knowledge of programming in Python
Good knowledge of machine-learning and artificial intelligence
Knowledge of fault detection in sensor data
Good analytical skills, initiative, and self motivation
Good command of the English language
Excellent teamwork and communication skills

Über uns

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options: https://go.fzj.de/womens-job-journey

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Master Thesis - Hybrid ML + LLM-based Fault Detection and Explainability for Smart Building IoT Systems

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