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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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analysis across case study regions. The successful candidate will work on the development and application of AI/Machine learning and behavioural modelling within the North and Baltic seas, utilising legacy
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Engineering, Physics, Applied Mathematics, or related discipline. Proven track record in numerical methods and computational fluid dynamics. Proven track record in machine-learning methods for computational
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, this PhD will explore machine-learning (ML) methods to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical
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to design targeted marketing campaigns. Causal Machine Learning is an emerging research field that can learn the causal effect of an intervention and how it varies within a population based on a large set of
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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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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology by: Developing
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posts,PHD Thesis Starting date: 30.10.2025 Job description: DESY Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of
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improvements in machine learning (ML) applications now allow researchers without extensive programming backgrounds to implement advanced image-processing techniques using accessible programming languages and