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high-resolution datasets on snow depth in Western Norway derived from machine learning and radar remote sensing. The successful PhD candidate for this position will work within the scope of the project
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modeling. These projects will focus on how to leverage ideas from a combination of partial differential equation based computational methodologies and machine learning techniques to develop computational
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project/work tasks: The SnowAI project aims to use to produce new high-resolution datasets on snow depth in Western Norway derived from machine learning and radar remote sensing. The successful PhD
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variety of related subject including: Machine learning and deep learning techniques, preferably with a focus on generative models (e.g. GANs, VAEs, LLMs, VLMs,). Robust data analysis methods and tools
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. Candidates should either hold a PhD in Computer Science, Information Technology, or a closely related field OR hold a PhD in any field in combination with strong computer programming and data visualization
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transport, health, energy, manufacturing, and smart cities. To be successful you will have: PhD in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field with focus
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, machine learning, deep learning, and optimization; Proficient in written and spoken English - essential for data analysis and communication with stakeholders Experience in proposal writing and funding
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Job Description Job Alerts Link Apply now Job Title: Research Analyst/ Associate/ Fellow in Machine Learning and Artificial Intelligence (ML/AI) Posting Start Date: 19/09/2024 Job Description: The
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. Conceptually, this includes data from a single experiment (regularization), across two experiments (registration), and for analyzing large datasets (statistical analysis and machine learning). This development
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from multiple disciplines and institutions. Required: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong background in machine learning / computer