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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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unique three-dimensional maps of neurotransmitter receptor distributions in the human, non-human primate and rodent brain Develop efficient processing pipelines enabling the spatial integration
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the vertical flux of organic matter in different oceanic regions. This will include the use of in situ camera systems, sediment traps, and bio-optical platforms to quantify particle abundance, size distribution
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/distributed programming and/or solid UNIX skills Practical experience with ML/DL workflows and common software libraries Your experience should be documented in research papers and Open Source code projects
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to emerging carbon dioxide removal techniques. To this end, distributed pelagic imaging techniques enable the sustained observation of aquatic life and its debris, comprehensively covering the earth’s water
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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modeling, AI-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based