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Field
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methods to rigorously assess the safety and effectiveness of medications in real-world patient populations. Defining individualized treatment strategies: Leveraging traditional and causal machine learning
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, checking, recoding data for analysis). At least intermediate knowledge of SAS or R programming required. Knowledge of Python and/or machine learning helpful but not required. The University of Miami offers
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biomedical image processing. Within the scope of machine learning and computer vision, there will be freedom to suggest your own research directions, and to become acquainted with new techniques and approaches
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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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profile PhD in Computer Science, Data Science, Machine Learning, or a related discipline. Proven experience in computer vision (e.g. image processing, deep learning, object detection, segmentation) and
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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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their work. Qualifications: PhD in Electrical and Computer Engineering, Biomedical Engineering, Mechanical Engineering or a related field. A combination of education and relevant experience from which
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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF