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UiO/Anders Lien 24th March 2026 Languages English English English Join the inclusive University of Oslo as a PhD Research Fellow in Machine Learning, tackling real-world data challenges! PhD
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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Babinski, PhD. This position will report to Research Professor Leslie Babinski. CIDR is a school-based research and professional learning initiative designed to strengthen adolescent wellbeing and literacy
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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators may be either tightly integrated with
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7
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Location Lexington, KY Grade Level 12 Salary Range $62,400-111,634/year Type of Position Staff Position Time Status Full-Time Required Education PhD Click here for more information about equivalencies: https
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 12 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