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Field
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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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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more
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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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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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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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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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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
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 17 hours ago
(e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in climate impacts in mountain regions complete your
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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