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the Neurogenesis and Brain Cancer group led by Prof. Simona Parrinello. The team uses a variety of state-of-the-art technologies, including advanced imaging, single cell and spatial ‘omics’, barcoding, mass
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novel machine learning-guided approaches. The position is located at TUM Campus Heilbronn. Your qualifications Strong background in computer science, AI, or related areas or similar fields. Solid
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registries, Patient-Centered Outcomes Research Institute (PCORI) projects, and investigator-initiated studies of novel biomarkers, diagnostic imaging and technology to capture and predict performance
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Research Studentship in ‘Deformation and fracture of TRISO fuel particles’ 3.5-year DPhil studentship Supervisor: Prof Dong Liu, Prof Emilio Martinez-Paneda About the Project The proposed PhD
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focuses on mechanical and morphological evolution of the insect heart, as part of the recently funded Human Frontier Science Program (HFSP) grant awarded to Prof. Young’s lab. The heart is one of the first
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the study’s infrastructure, improving system operations, and ensuring efficient processing of multi-source data. About You You will hold a Bachelor's degree (Master’s preferred) in computer science, data
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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processing in the mammalian cochlea in vivo , and how these influence central auditory neuronal pathways. The project will primarily involve using in vivo 2-photon imaging and AAV-gene delivery applied to a
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 27 days ago
develop our state-of-the-art imaging systems by optimizing the hardware and integrating real-time data processing and analysis through machine learning techniques to achieve precise characterization