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, dimensionality reduction and/or machine learning methods (e.g., Lasso, ridge regression) is highly desirable. Familiarity with neurostimulation, Parkinson’s disease, or neuropsychological assessment tools is
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preference over external candidates. For questions about the vacancy, you can contact: Claire Stevenson, c.e.stevenson@uva.nl . Where to apply Website https://www.academictransfer.com/en/jobs/357583/phd
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
establish reference performance and guide the design of more advanced models. The core of the work will then focus on developing and evaluating machine-learning-based NILM methods tailored
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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned
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journals and present at international conferences. Where to apply Website https://www.academictransfer.com/en/jobs/357570/phd-on-mixed-signal-circuit-des… Requirements Specific Requirements A master’s degree
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high-impact journals and present at international conferences. Where to apply Website https://www.academictransfer.com/en/jobs/357571/phd-on-mixed-signal-circuit-des… Requirements Specific Requirements A
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims