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Field
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. ICDS seeks outstanding early‑career researchers with expertise in Artificial Intelligence and Machine Learning in the following computational and data‑driven discovery areas: Earth Science Computational
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, machine learning, and multi-omics technologies to drive discoveries that have the potential to transform cancer diagnosis, treatment, and patient outcomes. This is an exceptional opportunity to create
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or more statistical or scripting languages, preferably R or MATLAB. Knowledge of survival-based statistical analysis, such as Cox regression and Kaplan-Meier analysis. Working knowledge of machine learning
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of scholars and a science support team. To complement this team, we are looking to hire a Postdoctoral Fellow in Social Reinforcement Learning and Human‑AI Hybrid Systems (E13 TVöD , 100%; 39 hours/week) The
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the range $106,293.57 - $113,659.72 + 17% super (Academic Level A) Based at our St Lucia Campus About This Opportunity We are seeking a highly motivated Postdoctoral Research Fellow to contribute
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: offshore wind turbines, wave tank experiments, fluid-structure interactions, sensors for offshore structural health monitoring, software development, machine learning and advanced AI modelling, and previous
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analysis and application of machine learning techniques to structured numerical and unstructured textual data; (d) have a good track record of academic writing, including report writing, manuscript
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for purposes of collective bargaining and matters affecting your compensation and working conditions. Basic Qualifications PhD in Computational Biology, Bioinformatics, Machine Learning, Data Science, or a
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applications for the position of Research Fellow . The Research Fellow (RF) will play a key role in advancing the research mission of NTU by supporting cutting-edge projects in computer vision, machine learning
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Location Code CHEMISTRY & BIOCHEMISTRY (02113A) Is this split and/or fully grant funded? Yes Duties and Responsibilities The Postdoctoral Scholar participates substantially in full-time, mentored research