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, numpy, scanpy, Squidpy, matplotlib, and others for single-cell and spatial analysis Interest in kidney research Exposure to machine learning and deep learning concepts Demonstrated ability to participate
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: MSc degree completed. Additional optional skills and qualifications: Previous research experience, particularly in the fields of Internet of Things security and machine learning models applied
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in the project proposal for Profile 7, in particular: Task3: Multimodal Data Analysis and Machine Learning; Task4: Coating Optimization and task: Dissemination. The work will focus on the study and
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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent
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(e.g. Interspeech, ICASSP, SSW) and contribute to open-source release of corpus and models. Qualifications Requirements A doctoral degree in speech technology, machine learning, computational linguistics
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structure-preserving, machine learning–accelerated scientific computing for plasma physics applications. In particular, the project involves developing data-driven collisional kinetic models and numerical