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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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Are you interested in challenging deep learning at its core? And specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision
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, Germany. We Offer You: A World-Class Environment: Access to a leading research environment specializing in hardware/software for medical wearables, translational endocrinology, and machine learning
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of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation of the mathematical models of the patho-physiology and PK/PD
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with machine learning. Self-Driving Laboratories (SDLs) are emerging research environments where experiments are planned, executed, and analyzed in closed-loop workflows that combine automated
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PhD Studentship in Aeronautics: Real-time machine learning and optimisation for extreme weather (AE0073) Start Date: Between 1 August 2026 and 1 July 2027 Introduction: Climate change is
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complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation
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Learning, Natural Language Processing, Human-Computer Interaction, Digital Health, Endocrinology Secondments (Preliminary Plan): UiB (Norway): 1–2 months — Patient and caregiver interviews, exploration
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Robotics, Mechatronics, Mechanical Engineering, CS, Automation, or similar Experience in at least one listed research area Motivation, curiosity, and ability to learn quickly Independence and hands
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. Research Fields: Artificial Intelligence, Multimodal Machine Learning, Natural Language Processing, Human-Computer Interaction, Digital Health, Endocrinology Secondments (Preliminary Plan): UiB (Norway): 1–2