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+49 241 80-49794
Lehrstuhl für Gebäude- und Raumklimatechnik
The E.ON Energy Research Center at RWTH Aachen University is focusing on sustainable energy supply concepts that take into account both technical feasibility and social and economic aspects. Reducing the primary energy consumption of buildings and increasing the indoor quality are among the central research tasks of the Institute for Energy Efficient Buildings and Indoor Climate. In the team Occupant Behavior and Comfort, the research focus is on the consideration of the interaction between energy system, system components and occupants as well as the provision of a healthy and comfortable indoor environment. The central objective is to reduce the energy demand while optimizing the indoor parameters that are decisive for comfort and health.
- Current studies in mechanical engineering, industrial engineering, computational engineering science or similar
- Ideally experience with Python and an interest in programming
- Independent and structured way of working
You are supporting the "FunkSTA" project. In this project, a method is being developed to detect and diagnose faults in the house transfer stations of district heating networks. For this purpose, measurement data is transmitted via wireless sensors to a cloud, from where it is available for processing. Your tasks are to support the development of a Python program for fault detection based on machine learning, which includes programming and evaluation, as well as supporting the team in data acquisition and processing. In your work, you will gain insights into intelligent data processing (data science), machine learning, fault detection, cloud technologies, and district heating operations.
The successful candidate will be employed as a student assistant.
The position is to be filled at the earliest possible date and offered for a fixed term of initially 6 months.
This is a part-time contract position.
The standard weekly hours will be 7-12 hours.
The number of working hours can be customised.
The salary is based on the RWTH Guidelines for Student and Graduate Assistants.
The position corresponds to a pay grade of 12,00 € per hour until 31.12.2023 and 13,00 € per hour from 01.01.2024.
RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung.
Application
Application deadline:
31/01/2024
Mailing Address:
RWTH Aachen University
Lehrstuhl für Gebäude- und Raumklimatechnik
Martin Rätz
Mathieustraße 10
52074 Aachen
Email:
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.