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fundamental and translational aspects of infectious disease (germfree/gnotobiotic animal facility, organoid cultures, T-cell engineering via CRISPR/Cas9 technology, in vivo imaging, animal models, microbiome
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imaging. Your Profile: * Master's degree in Computer Science, Electrical and Computer Engineering, Mathematics, Physics, or a related field * Strong background in mathematical and computational sciences
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
3D and image-based computer vision Experience implementing 3D computer vision algorithms and training end-to-end machine learning models (from data collection and design to evaluation) Knowledge and
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Skills/Qualifications Must have, at the start of their PhD programme, a Master (or equivalent) degree in Mechanical Engineering, Physics or Photonics with solid knowledge of optics and its applications
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sensing of atoms in the MLT. The lidar will be used for the first dedicated search for atomic species that are so far undetected in the interface of atmosphere and space. Modern image analysis tools shall
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of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g., SEM
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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image
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Chair of Biological Imaging 02.02.2026, Academic staff We are looking for a candidate (m/f/x) who will use the combination of our spectroscopy infrastructure, and structural information