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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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river valleys); • Identify stylistic patterns and regional variations in schematic rock art; • Apply machine learning tools for large-scale stylistic classification; • Establish a robust chronological
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combinations of structural and functional properties, using both simulations for machine learning and experimental validation. Fabrication tools and methods are already established in our laboratory. Key
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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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experimental workflows for generating and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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in the Nurse Anesthesiology Programs(see website: http://www.barry.edu/about/mission/ Teach anesthesia principles and basic sciences in didactic, simulation, and clinical settings and advise students
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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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compliance, if applicable). Does this position have supervisory responsibilities? No Preferred Education/Experience Bachelor’s degree in Computer Science, Machine Learning, AI, Data Science, Engineering
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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