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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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Scheduling, Real-Time Systems, Network Calculus, Robustness, Machine Learning, Industrial Networking Note: This thesis topic may not be appropriate for candidates seeking a career in the data and AI domain
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from information and coding theory, machine learning, and distributed algorithms. The project is in collaboration with Linköping University, which includes opportunity for research visits. The project is
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on novel applications of machine learning techniques on mobility data towards resilient, safe, inclusive and sustainable urban micro-mobility systems. You will become member of an international, 38-partner
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undergraduate education that embraces the teacher-scholar model and provides engaged learning experiences in the classroom. Interested candidates should complete the online application and submit a letter of
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Learning, or a closely related field. Strong understanding and demonstrated track record in protein structure modelling methods, with hands‑on experience in protein or biologics design and engineering. Hands
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the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en The position In this role your responsibility is
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structure prior to chromosome segregation, a topic they continue to investigate. Approaches include genetics, spatial genomics, single-molecule biophysics, super-resolution imaging, computational modeling
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machine learning or AI methods applied to imaging. Research Data Management and documentation practices Statistical Analysis & Experimental Design Technical Communication (reports, publications
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time scales. To do this, we will build on a landscape picture of stochastic gene expression dynamics inferred from data using modern machine learning techniques. The results will inform us about how