PhD Thesis: Collaborating autonomous IoT systems

Mode of Employment: Limited, Part-time 17,5 h/week Headed to the future? Hop right in. Industrial use cases require dependable wireless connectivity. However, quantifying and fulfilling dependability is a challenge in complex communication systems envisioned for future disaggregated and open campus networks. These systems consist of a multitude of orchestrated communication solutions (e.g., 5G and beyond, industrial WLAN) and distributed processing capabilities and services (e.g., edge computing, AI/ML as a Service, positioning), with a tendency towards disaggregation and open communication interfaces as proposed under the term open RAN (open Radio Access Networks). Shaping the functionality, architecture, and interfaces of future industrial campus networks constitutes a great opportunity to ensure dependability right from the beginning. What part will you play? Future autonomous IoT systems will rely on local wireless connectivity and edge computing to perform collaborative tasks ( hexa-x.eu ). This work shall investigate how a-priori information, such as knowledge about the task, the physical environment, and the state of the communication network, can be used to adjust connectivity parameters and/or reduce the amount of information exchanged between collaborating agents. The starting point is distributed/federated machine learning; however, it is crucial that constraints to communication and computational power are considered. Therefore, the following research topics are the focus of your PhD thesis: How can appropriate context information be collected over wireless interfaces? How can collaborative machine learning agents build, represent, and share \'experiences\' under constrained and unreliable communication conditions? Related research areas will also be addressed in this context, such as Joint Communications and Sensing, Distributed Machine Learning, Semantics, Digital Twin, D2D Communications, and Local Compute Integration (Edge). We don’t need superheroes, just super minds. You have successfully completed your master's degree in electrical engineering, ideally with a focus on communications engineering, or in a comparable field with above-average grades. You have very good programming skills in Python, and you are familiar with Linux. Ideally, you have knowledge of wireless standards, such as Wi-Fi, 5G, Bluetooth. Knowledge of Artificial Intelligence/Machine Learning, e.g., Distributed Learning, Federated Learning, would be a plus. If you have experience with Machine Learning frameworks, e.g., PyTorch, TensorFlow, this is a plus. Ideally, you have some experience with ns-3 or OMNET++ and would like to contribute your knowledge to us. You bring passion for solving real-world problems, have a strong willingness to perform and enjoy discovering new things as well. Very good written and spoken German or English skills complete your profile. Make your mark in our exciting world at Siemens. www.siemens.de if you wish to find out more about the specific business before applying. If you have more questions, please contact: www.siemens.de/fragenzurbewerbung www.siemens.com/careers if you would like to find out more about jobs & careers at Siemens. As an equal-opportunity employer we are happy to consider applications from individuals with disabilities. Organization: Technology Company: Siemens AG Experience Level: Early Professional Job Type: Part-time