MSc Thesis (jointly with Carl Zeiss Meditec AG): Large language models to streamline scientific research workflows

This collaborative research project will explore the use of conversational AI to streamline scientific research workflows. Emphasis will be placed on the use of large language models and innovative data storage solutions to enable human interaction with large scientific databases. Building upon initial results, the project will further explore the ability to integrate continual learning with the developed tools. The prospective student work in the AI and Machine Learning R&D team at Carl ZEISS Meditec AG, while also being part of the Lab for AI in Medicine at TUM.

Your qualifications:

• Advanced knowledge of machine learning and image processing.
• Demonstrated prior research experience in one of the fields of deep learning, computer vision, natural language processing or robotics.
• Excellent programming background in Python as well as PyTorch or Tensorflow.
• Strong collaboration skills and written and spoken proficiency in English.
• Full-time commitment to your Master’s thesis research.
  

Our offer:

• Be part of an exciting collaboration between academia and industry and work with experts in machine learning from TUM and Carl Zeiss Meditec AG.
• A contract and salary as student employee at Zeiss.
• An exciting research project with many opportunities to bring in your own ideas.
• Close supervision and access to state-of-the-art computer hardware.
  

To apply please send an email Christoph Dinh (christoph.dinh@zeiss.com), Raja Judeh (raja.judeh@zeiss.com) and Martin Menten (martin.menten@tum.de) with your CV and a recent transcript of records.