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University Medical Center of the Johannes Gutenberg University Mainz | Mainz, Rheinland Pfalz | Germany | 3 months ago
), is offering a fully funded PhD position in the area of statistical learning, machine learning, and survival analysis applied to large-scale proteomics and multi-omics cohort data. The PhD project
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) and Artificial Intelligence (AI). The Department envisions to cultivate a comprehensive curriculum that encompasses key research pillars such as Big Data Analytics and Management, Machine Learning 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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computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The subject area concerns
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of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML
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, Search and Recommendation, Data Science, Machine Learning, and Big Data Analysis, Distributed Computing and Cybersecurity Human-Computer Interaction. SCT will fast-track digital innovation across all
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cybersecurity expertise with modern AI techniques such as machine learning, deep learning, or large language models? Then we strongly encourage you to apply. You will join an established team with 25+ members
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and colleagues. Job Requirements: Required Qualifications: PhD in Human Computer Interaction, Computer Science or a related field by time of appointment Documented teaching and research ability
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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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in exercise and dance interventions. Build and evaluate AI / machine learning models using labelled, collected multimodal data to classify motor and non-motor symptoms, identify digital biomarkers