Edge and Industrial Network Systems Research Internship

About the role

Siemens Research & Predevelopment (RPD) is the central R&D department of Siemens and plays a key role in shaping the future of our products. RPD acts as a strategic partner to support the executive units of Siemens. The main research focus is on future technologies for industry, infrastructure, mobility, and healthcare.

Responsibilities

• Research, design, and prototype methods for scalable industrial edge and networked software systems, with emphasis on connectivity, interoperability, reliability, performance, and maintainability in shopfloor environments.
• Build and evaluate edge application workflows involving components such as device management, data brokers, industrial data ingestion pipelines, event-driven processing, dashboards, and notification services.
• Investigate architectures and design patterns for distributed edge systems, including secure communication, message-based integration, application deployment, observability, and runtime monitoring across connected industrial assets.
• Prototype solutions in C#, Python and related technologies to support edge analytics, automated reporting, equipment efficiency monitoring, and end-to-end industrial data flows across edge and cloud-connected environments.
• Collaborate with researchers and engineers to define milestones, run experiments, analyze system behavior, and translate research insights into scalable industrial software concepts and product-relevant innovations.

Qualifications

• Currently enrolled in a Master’s or PhD program in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Networking, Cyber-Physical Systems, Industrial Informatics, or a closely related technical field.
• 3+ years of research or hands-on experience in edge computing, distributed systems, computer networking, industrial IoT, cyber-physical systems, or industrial software systems.
• Programming skills in C#, Python and experience developing software prototypes, system integrations, or data-processing pipelines.
• Understanding of computer networking fundamentals, including TCP/IP, routing, switching, DNS, firewalls, VPNs, network segmentation, and secure communication across distributed systems.
• Hands-on experience with networked systems, industrial communication environments, or edge-to-cloud connectivity, including troubleshooting, performance analysis, and reliable data exchange across heterogeneous devices and services.
• Experience working with data collection, analytics, or monitoring systems in industrial, IoT, edge, or networked environments.
• Hands-on experience with modern software engineering workflows and CI/CD practices, including Git, automated testing, build and release pipelines, and deployment processes for distributed, networked, or edge-based applications.
• Proficient in English, both written and verbal.

Preferred Skills

• Research or hands-on experience with industrial edge platforms, industrial IoT architectures, edge orchestration, or distributed application deployment.
• Familiarity with industrial connectivity technologies and protocols, such as MQTT or similar OT/IT integration approaches.
• Experience with industrial and enterprise network architectures, including OT/IT integration, edge network design, secure remote access, VLANs, NAT, MQTT-based communication, connectivity, or similar industrial networking technologies.
• Familiarity with network observability and diagnostics tools such as packet capture, protocol analysis, traffic monitoring, latency profiling, or distributed communication debugging in complex edge or industrial environments.
• Experience with containerization and deployment technologies such as Docker, Kubernetes, or cloud-edge deployment workflows.
• Experience with observability, logging, trace-based monitoring, runtime diagnostics, or performance analysis for distributed systems.
• Excellent problem-solving skills, attention to detail, and ability to quickly learn and apply new technologies, tools, and research methods.
• Strong written and verbal communication skills, with the ability to articulate complex technical concepts to research and engineering audiences.