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engineering (focusing on deep learning for computer vision), and the division of statistics and machine learning at the department of computer and information science (focusing on the theory behind machine
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disorder. This project investigates early neural markers of psychosis by integrating multimodal neuroimaging with genetic and transcriptomic data and applying machine-learning approaches to identify
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machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
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of reports and scientific papers References Shunlei Li, Ajay Gunalan, Muhammad Adeel Azam, Veronica Penza, Darwin G. Caldwell, Leonardo S. Mattos, “Auto-CALM: Autonomous Computer-Assisted Laser Microsurgery
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Computer-Assisted Laser Microsurgery,” IEEE Transactions on Medical Robotics and Bionics, https://doi.org/10.1109/TMRB.2024.3468385 , 6(4), pp. 1423-1435, November 2024 ESSENTIAL REQUIREMENTS PhD degree in
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chemistry, from the use of advanced electronic structure methods to the development of dynamical approaches to study photochemical reactions, also including machine learning. The group is part of the Cluster
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flexibility orchestration Scalable data and machine learning pipelines Digital twin architectures for cyber-physical energy systems AI-based energy system modeling, simulation, and optimization Secure and
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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incremental optimization. We seek researchers to develop next-generation machine learning methods that fundamentally rethink how large-scale AI systems are trained, fine-tuned, and deployed. Our focus is on
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be