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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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automation integration and deployment of image segmentation algorithms for the automated assessment of thin-film solar cell fabrication processes (e.g. layer quality, defects, morphology) within NOMAD Oasis
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Package: Actively participate in a participant-driven co-design process to develop a framework for returning molecular and imaging data to study participants Contribute scientific content to patient
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projects within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or
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seek for the following capabilities: • PhD or Master in Biology, Biophysics, Biochemistry, Bioengineering or related topics. • In vivo imaging experience, preferably optical, ultrasound or even photo
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flow characteristics from X-ray and electron images integration of motion analysis and digital volume correlation processing of images in preparation for image-based modelling Your profile PhD in physics
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Max Planck Institute for Medical Research, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 1 month ago
Developing new fabrication processes for CaF₂, sapphire, and BK glass Collaborating closely with industry partners in areas including lasers, imaging cameras, and display technologies Preparing and supporting
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the excellence cluster Your profile PhD in physics or in a related discipline experience in phase contrast or coherent X-ray imaging advanced programming skills in a high-level computer language (Python or related
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Chair of Biological Imaging 30.01.2026, Academic staff Researcher (m/f/x) with an engineering or physics background and a motivation to drive the technology towards the market. The lab The Stiel Lab
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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