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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques
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modelling and machine learning to join and lead a dynamic international team of early-career researchers. This exciting role is part of a cutting-edge project investigating the structural integrity
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in the western US. We lack timely forecasts of direction and rate of disease spread during an outbreak event. Modeling approaches will feature process-based machine learning in high-performance
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 23 hours ago
data sharing (preferred); good knowledge of machine learning algorithms; proficiency in high-level programming languages (e.g., C++, Python, C#, etc.) (preferred); knowledge of database formulation and
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candidate will report to the Principal Investigator (Director of AI Research at OVCARE, Dr. Ali Bashashati). Responsibilities Designs and implements machine learning models for bulk and single-cell genomics
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory Science – Leveraging drug development and regulatory
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expertise in the following areas: Machine Learning in general, with an emphasis on deep learning and language modeling Model benchmarking and evaluation pipelines for NLP/LLMs Domain-aware application of AI
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Are you an atmospheric scientist looking to apply your expertise to real-world forecasting challenges in Africa? Machine-learning has the potential to revolutionise weather prediction in Africa, and
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent