Germany Job Openings

Fraunhofer-Institut für Integrierte Schaltungen IIS

Student Assistant (m/f/d) - Data Science & Machine Learning Projects (Domain Adaptation, Transfer Learning, Object Detection)

Munich

FULL TIME & PART TIME

October 7, 2024

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 32 000 employees work with an annual research budget of 3.4 billion euros.
The »Analytics« department at the »Center for Applied Research on Supply Chain Services« at Fraunhofer Institute for Integrated Circuits IIS develops new methods and processes for application-oriented data analytics and AI. You would be applying to the »Data Efficient Automated Learning« group located in Munich, which has a strong focus on Machine Learning (ML) and its applications. We focus on reducing the high cost of annotating large amounts of data (Data Efficiency) and the high manual configuration effort associated with ML development (Automated Learning).
Are you interested in combining research with practice and advancing your skills in the field of Artificial Intelligence (AI) and Machine Learning?
Then have a look at our offer!
What you will do
  • You will mainly support our team with research projects in fields such as Object Detection, Domain Adaptation, Transfer Learning
  • You will conduct new research and summarize existing research or scientific writings
  • You will work on the development and maintenance of an extensible ML pipeline within a collaborative software team (e.g., training, validating, and deploying ML models)
  • You will perform classical data science tasks such as data exploration, data cleaning, data analysis and visualization
  • You will assist with administrative tasks (client presentations, documentation)
What you bring to the table
  • You are enrolled in a master’s program or nearing completion of your bachelor’s degree in Statistics, Computer Science or Data Science, Mathematics or a comparable field. Applicants that have experience in the fields of Remote Sensing, NLP, Active Learning or Semi-Supervised Learning are encouraged to mention this in their application letter
  • You possess working knowledge of Python and especially in frameworks such as Py Torch, sklearn, etc.
  • You exhibit a strong understanding of concepts in ML and Statistics and show interest in current ML research
  • You have initial experience with Git, container technologies (Docker, etc.)
  • You demonstrate initiative and an independent working style
  • You are proficient in German and/or English
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 10 to 20 hours a week or as an intern for a period of at least three months ). 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 would be happy to offer you the opportunity to write a bachelor's or master's thesis in cooperation with us in the above-mentioned subject area. The thesis will be assigned and carried out in accordance with the rules of your university. For this reason, please discuss the thesis with a professor who can advise you over the course of the project.
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.
Interested? Apply online now (PDF: cover letter, CV, transcripts). We look forward to getting to know you!
Anne Klier
Fraunhofer-Institute for Integrated Circuits IIS
www.iis.fraunhofer.de/en
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