Scientific Employee for the Design of Intelligent and Resilient Production Systems (m/w/d)

About us

The Institute of Automation and Information Systems is one of the leading institutes for software engineering in automation. We are part of the TUM School of Engineering and Design and maintain strong links with the computer science community. One of our key research areas is the design and operation of intelligent networked production systems. In the competitive globalized economy and with an increased need for sustainability and resource-efficiency, the resilience of such production systems is key, achieved by advanced means of Fault-tolerant Control, including the avoidance and automatic recovery of faults. Especially faults on the field-level are oftentimes the reason for downtime, requiring resilient and intelligent field-level devices. Due to real-time constraints, the decision-making process on the field-level has to be highly efficient, necessitating appropriate information representations and algorithms. On the machine-level, (semi-)automatic recovery from faults and restarts have a huge potential for increasing the Overall Equipment Effectiveness. The design of such resilient systems is complemented by alarm analysis, e.g., root-cause analyses, which we investigate regarding implementation both within the field-level and using an architecture for distributed computing between field, edge, and cloud-level devices. Thereby, scalability in horizontal (additional cloud-connected processes) and vertical direction (more complex process observation, prediction, and intervention) are essential for a continuously expanding intelligent reconfigurability platform. We are currently looking for a PhD candidate to join our motivated team in this research area.

 

Requirements

  • M.Sc. or Dipl. Degree in mechanical engineering, electrical engineering, computer science or equivalent
  • Strong technical background in automation, including PLC programming and decentralized production using Multi-Agent Systems and related frameworks, e.g., JADE/ PADE
  • Background in data science, specifically alarm analysis, is a plus
  • Programming skills, especially IEC 61131-1 and a high-level programming language such as C#, Java, or Python
  • Practical experience with cloud platforms (AWS, Azure) and communication protocols (AMQP, MQTT, OPC UA) helpful
  • Interdisciplinary cooperation and communication skills
  • Very good writing and presentation skills in English
  • Prior publications are beneficial

Tasks

  • Research and prototypical implementation of networked systems with a focus on the field-level of production systems
  • Design of resilient production systems
  • Close cooperation with related research fields, e.g., Data Analytics and Model-Based Systems Engineering at the institute and with our project partner
  • Evaluation of the results, both in an academic setting using demonstrators and in an industrial setting with industry partners
  • Lecturing and lecture preparation
  • Supervision of student theses
  • Various research related tasks, such as proposal writing

What we offer

  • Exciting, diverse, and self-dependent working environment
  • A highly motivated, and interdisciplinary team
  • Option to pursue a Ph.D.
  • Salary in accordance with the German state regulated public service salary scale (TV-L E13)

Note that applicants with severe disabilities will be given priority consideration given comparable qualifications. Also, TUM is an equal opportunity employer. TUM aims to increase the proportion of women and therefore particularly welcomes applications by women.

Application

Please send your letter of application, your curriculum vitae, copies of key documents, such as transcripts and degree certificates, a list of publications, further documents and references as a single PDF document to sekretariat.ais@ed.tum.de and clearly indicate your name and contact information

For more information, see www.mec.ed.tum.de/ais

If you apply in writing, we request that you submit only copies of official documents, as we cannot return your materials after completion of the application process.

As part of your application, you provide personal data to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application you confirm to have read and understood the data protection information provided by TUM.