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Experience with using inference/machine learning tools and basic programming is a plus As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe
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Experience with using inference/machine learning tools and basic programming is a plus As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe
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, machine learning, and programming (preferably Python) is highly valued. Effective communication with clinicians and interdisciplinary researchers is crucial, and excellent proficiency in English is required
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to participate in the creation of complex machines that have never existed before? Do you enjoy sharing your knowledge with younger group members? If yes, then maybe you want to work as a research assistant. The
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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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Are you eager to support exciting research with ultracold atoms and trapped ions? Do you want to participate in the creation of complex machines that have never existed before? Do you enjoy sharing
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such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary geospatial or remotely sensed data. Quantifying uncertainty and correcting
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, Industrial Engineering, or related discipline; Affinity and/or experience with computer programming, statistical learning, and optimization techniques; A good team spirit and feel at home at the intersection
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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scans and use advanced data-driven methods, including artificial intelligence (AI) and machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology