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Field
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biosignals. Application of machine learning techniques for classification of different classes using the extracted features. Assembly, documentation, testing, and use of an innovative biosensing system
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We
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. Advanced machine learning, reinforcement learning, and agent-based optimization techniques will be developed to reduce voltage deviations, cut active power curtailment, and improve system adaptability under
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1 Sep 2026 Job Information Organisation/Company University of Minho Department Centro ALGORITMI Research Field Engineering » Computer engineering Researcher Profile Other Profession Positions
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boosting, and related machine-learning approaches Evaluation of model generalizability using train/test splits, leave-one-cohort-out validation, and leave-one-platform-out validation Assessment of predictive
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Design-Build-Test-Learn (DBTL) cycle that rapidly iterates the design, synthesis, and evaluation of molecular-robot components. https://molbot-ex.org/index.html [Work content and job description] The E01
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex network models to partially observed hospital infection data, leveraging patient movement data. This research will
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic