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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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focus on understanding how axons maintain their structure and function, and how these processes break down in disease. You will have the opportunity to contribute to one of our ongoing projects addressing
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focus on research and development in Atmospheric Pressure Matrix-Assisted Laser Desorption/Ionization (AP-MALDI) mass spectrometry and molecular imaging, using high-resolution Orbitrap MS instrumentation
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing