Doktorand Corporate Research & Technology (f/m/x)
We are seeking a passionate and talented graduate who wants to make an impact in the field of computer vision and machine learning to enable next generations of purposeful applications. For three years you will work on advancing the state-of-the-art on vision foundation models for applications with non-standard images, e.g., recordings in medical healthcare, in life sciences, or in semi-conductor industry applications. The purpose of this PhD research project is to enable scenarios where image analysis solutions need to be configured for different usecases without expensive re-training but via different prompt types (examples, text, etc.) and where domains can change between training and application. You will have the opportunity to simultaneously work and receive guidance from two top research teams: a fast-growing team of machine learning scientists and research engineers at ZEISS Corporate Research & Technology, and the Computer Vision Group Jena headed by Prof. Joachim Denzler. In addition, you will have the chance to interact with our corporate partners and collaborators, gaining valuable industry experience and networking opportunities. Following our dedication to science, you will also publish and present your research results at international conferences and venues.
Excellent master’s degree in computer science, robotics or comparable subjects
Solid understanding of computer vision and deep learning fundamentals, ideally first experience with transformer architectures
A passion for programming with a solid background in Python and hands-on experience with machine learning frameworks such as PyTorch
High intrinsic motivation, a creative mind and a structured way of working - both independently and within a team environment
Good communication and presentation skills in German and English
Send us your application together with your transcript of records and other certificates. ?We look forward to receiving your application.
Your ZEISS Recruiting Team:
Katharina Dandorfer