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) distributional generalization, transfer learning, causality Multi-objective settings and alignment, RL theory Statistical learning theory, optimization (e.g., implicit bias) Robustness (broadly defined), privacy
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-armed Bandits, Bayesian Optimization. Automated Model Design and Tuning: Neural Architecture Search, Hyperparameter Optimization. Computer Networking: Resource-Constrained Networking (e.g., Internet
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/Seurat, count models, batch correction, differential analyses). Strong grounding in statistics (GLMs, hierarchical/Bayesian modeling, multiple testing) and experimental-design principles. Bioinformatics
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/Seurat, count models, batch correction, differential analyses). Strong grounding in statistics (GLMs, hierarchical/Bayesian modeling, multiple testing) and experimental-design principles. Bioinformatics
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focus on developing innovative multifunctional coatings with integrated antimicrobial properties. Key objectives include: Design and synthesis of multifunctional antimicrobial coatings. Materials and
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of this position is to establish advanced in vitro simulation models for vascular grafts to assess the performance of nanoengineered antimicrobial and antifouling coatings. Key objectives include: Development
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-armed Bandits, Bayesian Optimization. Automated Model Design and Tuning: Neural Architecture Search, Hyperparameter Optimization. Computer Networking: Resource-Constrained Networking (e.g., Internet
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and a sustainable circular economy in Europe. Job description of the PhD Position Key objectives of this position include: – Develop electrically conductive lignin-bio-fiber materials by utilizing
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antimicrobial properties. Key objectives include: Design and synthesis of multifunctional antimicrobial coatings. Materials and physicochemical characterization of the fabricated coatings. Exploration of how
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establish advanced in vitro simulation models for vascular grafts to assess the performance of nanoengineered antimicrobial and antifouling coatings. Key objectives include: Development of an in vitro model