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areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and
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. Knowledge of data-driven analytics, machine learning, signal processing, or advanced modelling techniques relevant to power systems. Experience with real-time simulation platforms, hardware-in-the-loop
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verbal, written communication skills In-depth knowledge of deep learning, specifically VLM models, computer vision techniques (e.g., open vocabulary object detection, model distillation, VQA, test-time
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the soil-water-plant-air continuum using process-based models. You will learn how to take proper soil, plant and air samples that influence carbon and nitrogen dynamics and learns how soil and plant
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Postdoctoral Fellow in Machine Learning and Digital Health Services for Frail Older People Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile
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conferences. About You You will be educated to doctoral level in Remote Sensing, Geography, Geoinformatics, Computer Science, Artificial Intelligence, Machine Learning or a related discipline. You will have
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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valuable for producing reliable climate projections, whether certain weather systems are fundamentally harder to model with machine learning than others, and whether we can develop emulators that can be
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Abilities: Proficient in data analysis, modeling, machine learning, and AI, using Python and SQL, with extensive experience in libraries and frameworks such as Pandas, NumPy, scikit-learn, Gensim, BERTopic
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; · Perform other duties and provide additional support as assigned. Knowledge, Skills, and Abilities: Proficient in data analysis, modeling, machine learning, and AI, using Python and SQL, with extensive