Mode of Employment: Limited
Part Time: 17,5 h/week
Headed to the future? Hop right in.
We are passionate about innovations that mean real progress. We are excited about technologies that still need to be developed. What about you?
The Internet of Things (IoT) links the physical world with the digital world, collecting data from assets in order to create value. The Industrial IoT (IIoT) applies this concept to Factory Automation, where so called, Smart Factory should run operations without much of humans intervention. Connecting physical devices in Smart Factory opens up new possibilities, but they also introduce new challenges. An increased number of connected and diverse devices (sensors, actuators, machines, and systems) create a complex communication infrastructure. They also generate a vast amount of data. But very often the meaning of the data is not clear, and relations among these devices are complex and not explicitly defined. All this represents a challenge when creating new value with IIoT. Thus, there is intent to move from connected devices toward Smart Devices.
Smart Devices are aware of their connections. They produce and consume data, which can be seamlessly comprehended by both machines and humans. Smart Devices are more autonomous in a sense that they can adapt to environmental changes and can decide and act accordingly. They also achieve goals, defined in a descriptive way as opposed to be prescriptively programmed. For all these features, Smart Devices need to rely on Knowledge Graphs - a structured knowledge about domain, environment, and functions provided in a machine-interpretable representation. Knowledge Graphs (KG) will be based on standardized information models, e.g. OPC UA information models. AI techniques of Machine Learning (ML) and Natural Language Processing (NLP) are another major building block underlying Smart Devices.
What part will you play?
You contribute to the applied research in the area of IoT, NLP, ML, and KG in order to realize Smart Devices
You actively drive the discussion on main research questions and their relevance for Siemens
You are involved to internal and public funded research projects
You secure your work through patent filings
You publish scientific publications in order to present and discuss your findings in internal and external communities
You supervise interns and master-students
We dont need superheroes, just super minds.
You already have a masters degree (or comparable) in Computer Science or related disciplines
You have a strong achievement drive and genuine desire to discover new things on your own
You bring a deep understanding of Machine Learning (ML) and Natural Language Processing (NLP)
You also have sound knowledge of Semantic Technologies
You have good interpersonal communication and presentation skills both in English and German
Make your mark in our exciting world at Siemens.
if you wish to find out more about the specific business before applying. If you have more questions please contact: [email protected]
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: Corporate Technology
Company: Siemens AG
Experience Level: Early Professional
Job Type: Part-time