Master thesis - Explainability in Recommender System (M/F/D)

fortiss is the research institute of the Free State of Bavaria for software-intensive systems and services with headquarters in Munich. The institute currently employs around 180 employees, who collaborate on research, development and transfer projects with universities and technology companies in Bavaria, Germany and Europe. Research is focused on state of the art methods, techniques and tools of software development, systems & service engineering and their application to reliable, secure cyber-physical systems, such as the Internet of Things (IoT). fortiss has the legal structure of a non-profit limited liability company (GmbH). Its shareholders are the Free State of Bavaria (as majority shareholder) and the Fraunhofer Society for the Promotion of Applied Research.

The mission of the Human-centered Engineering (HCE) at fortiss is to develop intelligent user interfaces and trustworthy AI systems. By utilizing machine learning techniques, our focus lies on the research into user-, domain- and task-models to ensure human-machine-interaction as natural and as robust as possible. Cognitive interaction is improved by integrating multimodal elements.

In this project, we search for a new team member:

Master thesis - Explainability in Recommender System (m/f/d)


Your tasks: :

  • Developing and evaluating explainability metrics of recommender system
  • Analyzing the state of the art and current research results
  • Implementing learning algorithm
  • Training based on data of recommender systems

Your profile:

  • Students in Computer Science or related technical disciplines
  • Good knowledge of human-computer-interaction, intelligent user interface and machine learning
  • Basic understanding of graph theory and graph representation learning would be a plus
  • Experience and practical proficiency with programming languages and tools (e.g. Python, C++, Git or Unix)
  • Analytical thinking as well as independent and structured work
  • Excellent communication and teamwork skills
  • (Very) good knowledge of English or German in both spoken and written

Our offer:

  • A dynamic work environment with highly qualified and motivated colleagues
  • Flexible working hours
  • Close collaborations with other leading research groups and industrial technology leaders in automotive, aerospace, energy, medical and industrial applications
  • Please note that this Master thesis is not remunerated

Did we catch your interest?

Please submit your application with a motivational statement, a detailed CV and a current transcript of records to our job portal.

Job-ID: HCE-ALL-BAM-01-2019

Contact:Mr. Zhiwei Han