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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 5 days ago
of critical thinking Experience with photonics, fluorescence, imaging or biochemical methods is helpful Our offer Highly motivated team Flexible working hours World-class institute with outstanding
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only
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extant taxa Perform collection visits to study and document fossil turtle specimens Process and analyze digital CT datasets of cranial and neurological structures Carry out geometric morphometric analyses
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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of electron microscopy imaging and spectroscopy to reveal the structure–property relationships that govern molecular adsorption mechanisms. This interdisciplinary project is fully funded by DTU’s PhD grant
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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are molecules that exist in two forms, referred to as enantiomers, each being a mirrored image of the other. Different enantiomers share the same physical properties, but often have starkly different biological
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, performing data collection and processing of cryo-EM data. Setup of future hardware and software as the research technology is upgraded. Providing lab members support in data collection, image processing, map
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, you need to develop and apply methods that enable the recognition of phenological stages of allergenic plants on images. Then, the phenological development of these species shall be modelled based