Our »Process Intelligence« group analyzes, designs and optimizes data-driven processes and supports companies with process-related key performance indicators and recommended actions for decisions in transportation, production, logistics and healthcare. To do this, we use qualitative and quantitative analysis and Machine Learning (ML) Methods. Our group is part of the Analytics department, which conducts research in the fields of analytics, artificial intelligence, and mathematical
optimization in the context of the digitalization of supply and value chains.
What you will do
• You independently develop existing Python code further or new ones, that we can use for future projects
• You mainly support the development of a collaborative generic codebase, built to be used on different input datasets
• You will process and analyze data and train reusable models on open source or project-specific datasets
• You will help implementing modern deep learning architectures for sequential data-analysis (LLM) in the context of Process
• You may assist in building internal infrastructure for big data analysis
What you bring to the table
• You are studying computer science, physics or mathematics or you have already obtained programming skills in addition
to another study program
• You already have practical experience in programming with Python, write reliable code and adhere to existing coding
standards and software engineering principles
• You already have some experience with ML and common ML frameworks (pytorch, tensorflow, keras, sklearn)
• You have optional experience in dealing with large amounts of data and containerization (Spark, Dask, Kubernetes, Docker)
What you can expect
• Flexible working hours
• Open and friendly team work
• Varied tasks with room for creativity
• Exciting seminars and events
• Networking with scientists
• Active contribution in applied research
• Interesting an innovative projects
Weekly working hours are determined by agreement. You can start from now on (as a student assistant from 12 to 20hours a week.) You can reduce your hours before exams and increase them during semester breaks. You can flexibly determine the working days. After your studies, you have the option of working with us full or part time.
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.
Apply online now (PDF: cover letter, CV, transcripts). We look forward to getting to know you!
Fraunhofer-Institute for Integrated Circuits IIS