Job ID: 483501 Posted since: 04-Nov-2025 Organization: Foundational Technologies Field of work: Internal Services Company: Siemens AG Experience level: Student (Not Yet Graduated) Job type: Full-time/Part-time Work mode: Office/Site only Employment type: Fixed Term Location(s): Garching - Bayern - Germany Mode of Employment: Fixed Term Are you ready to revolutionize wireless communication in industrial environments? Join us as a Master Thesis student at MCH GCH, diving deep into "Site-Specific SNR Distribution Estimation Using Gaussian Mixture Models". Embark on a journey where your research will pave the way for next-generation network configurations and quality of service in dynamic factory settings. What we offer you Factory halls are especially challenging environments for reliable wireless communication, because of their high dynamicity level, the existence of many moving machines and metal surfaces, which cause many reflections, high multi-path fading effects to the wireless signal. Having an as-precise-as-possible factory-site channel description will enable the computation of a precise QoS-profile across the shop floor and influence the process of factory hall and network design. The nodes placement or repositioning, such as navigation and control of AGVs and AMRs (autonomous mobile robots) can be triggered by the decisions and observations done by a (network) DT. The goal of this thesis is to obtain a site-specific SNR distribution estimation. By means of a link-level simulator (e.g. Sionna by NVIDIA), we plan to use ray-tracing for a particular given digital representation of the environment in order to compute the channel impulse response. Exciting research and development projects that put your theoretical knowledge into practice Individual supervision and support from experienced experts in your field Access to the latest technologies, laboratories, and resources Diverse opportunities to contribute your ideas and actively shape the projects Excellent career opportunities through contact with potential employers You'll make an impact by You will initially create a detailed 3D model of the laboratory environment using Blender or similar software, which includes the dielectric properties of objects to accurately simulate wireless signal behavior Subsequently, you will employ the Sionna ray-tracing tool to compute the channel impulse response (CIR) from the 3D model, aiding in the accurate estimation of power delay and phase delay profiles Using Gaussian Mixture Models (GMM), you will analyze the CIR data to approximate the Signal-to-Noise Ratio (SNR) distribution and the envelope of wireless channel propagation within the factory environment You will set up a simulation grid to calculate CIR for all possible transmitter-receiver pairs in your environment, deriving block error rates (BLER) using a physical abstraction model from Sionna or related frameworks Finally, you will validate your findings on real test beds using Universal Software Radio Peripheral (USRP) devices, confirming the accuracy of your power delay profile and SNR distribution under various testing scenarios This is how you'll win us over Education : You are currently successfully enrolled in a master's program in Electrical Engineering, Informatics, or a related study program with a background in wireless communication Experience and Skills : Proficiency in Blender or similar software for 3D model design and experience with Sionna or USRPs is advantageous Strong analytical and mathematical skills, particularly in optimization and machine learning methods, including Gaussian mixture models Solid programming skills in Python and C++ Ways of Working : You exhibit self-initiative and the ability to work independently, especially when solving complex problems Languages : Excellent English skills, both written and spoken, with strong scientific writing capabilities You are much more than your qualifications, and we believe in the potential of every single candidate. We look forward to getting to know you! Your individual personality and perspective are important to us. We create a working environment that reflects the diversity of the society and support you in your personal and professional development. Let’s get to know your authentic personality and create a better future together with us. As an equal-opportunity employer we are happy to consider applications from individuals with disabilities. About Us The world never stands still. And new challenges arise every day. With a passion for questioning things, for supplying ideas, and intelligently driving things forward we are helping society move towards a smarter tomorrow. Be it with technologies that reduce carbon emissions in cities or hyperintelligent robots. This is how we are able, to tackle the most important projects and push them forward together. Help us shape the future. www.siemens.de/careers – if you would like to find out more about jobs & careers at Siemens. 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