We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. #STUDENT ASSISTANT NETWORK FULL#After your studies, you have the option of working with us full or part time.įelix Kreyß ( will be happy to answer any questions you may have about this position. You can flexibly determine the working days. You can reduce your hours before exams and increase them during semester breaks. The duration for an internship is at least three months. More information about our employer offers on our website: Weekly working hours are determined by agreement, minimum are 10 hours per week. Mentoring program »josephine©« for talented female students.Active contribution in applied research.You have the ability to work independently.You have experience in routing (OSI Layer 3) and network programming.You have programming skills in Linux (preferred) or similar.You are currently studying electronics and information engineering, computer science or a similar field.Optional: You develop a multihop capable adaptation.You extract relevant network data and provide them by an API.You distribute tasks and data over these devices in a singlehop manner.You combine distributed IoT Devices to a sovereign and decentralized ad-hoc network.You detect and track available wireless devices (raspberry 4) due communication protocols (WiFi, Bluetooth.You like to design and realize a network management for a demonstrator with distributed and heterogeneous components using decentralized approaches? #STUDENT ASSISTANT NETWORK HOW TO#The objective is to develop a new technique to give access to idle resources on small devices and ask ourselves how to improve technical benchmarks like availability, latency or channel utilization as well as social benchmarks like privacy, green communications or even user experience related to state of the art wireless IoT-communications. Within the research project digital signal processing with artificial intelligence (DSAI) the Fraunhofer IIS has a decent view to the field of network orchestration for distributed machine learning tasks on the extreme edge.
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