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patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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Website https://www.academictransfer.com/en/jobs/358703/phd-in-scalable-safe-ai-for-sem… Requirements Specific Requirements A master’s degree AI, Machine Learning, Data Science, Computer Science or a
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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Engineering, or a closely related field. Required qualifications for graduate teaching include a PhD or terminal degree in Computer Engineering, Electrical Engineering, or a closely related field (preferred
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 27 days ago
-throughput screening; - Cell painting assays and high-content image-based analysis (e.g., CellProfiler, Harmony); - Machine learning models for antimicrobial activity prediction (e.g., Weka); - Strong
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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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preferred Excellent knowledge of microeconometric methods for causal inference; knowledge of machine learning methods is preferred Experience in university teaching Strong communication and teamwork skills