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analysis utilizing methods rooted in artificial intelligence (i.e. machine learning and deep learning). The analysis will be the basis for developing a predictive model to help select the most optimal method
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expertise. Most of the skills needed (e.g. geospatial analysis, data handling, programming, and landslide‑hazard concepts) can be developed during the PhD with support from the supervisory team and training
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detection, and Klepsydra Technologies handles algorithm deployment and acceleration on embedded hardware. Key Responsibilities • Analysis of failure modes for rocket propulsion systems • Contribution
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skills Biomedical Data Science UG degree: List A List B Introduction to Medical Ethics Python language programming Probability theory, statistics and Bayesian analysis Artificial intelligence in Medicine
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computational tools for automated imaging analysis of neurodevelopmental disorders. Genetic testing has transformed our understanding of neurodevelopmental epilepsy. Identification of common genetic mutations in
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PhD Studentship: Enhancing Material Properties and Longevity in Maxillofacial Reconstructive Devices
, or other programmes with a focus on material testing and analysis. Desirable: MSc or MRes in a relevant discipline such as additive manufacturing, medical devices, or materials science; dental or medical
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into the transport, deposition, and long-term storage of plastics in the deepest parts of the global ocean. Relevant experience in (micro)spectroscopic analysis, image analysis, or environmental particle analysis will
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Dortmund, we invite applications for the Research Group Analysis of Microscopic BIOMedical Images (AMBIOM): PhD Candidate (m/f/d) The position is part of the DFG-funded project: ComplexEye - a 96/384-well
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Systems (GIS) and large-scale spatial and environmental pattern analysis. They will also be responsible for participating in soil sampling teams and in the design of large-scale monitoring networks. With
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data