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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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inference methods, survey design, and/or machine learning Experience with web scraping and API-based data collection Organizational and coordination skills, such as assisting in drafting terms of reference
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well as to develop new courses in areas such as statistics, data science, machine learning and risk analysis. The department has long-term teaching obligations in NHH’s bachelor program in economics and business
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disciplines, including human-robot interaction, robot learning, soft robotics, computer vision, and agricultural robotics. About the PhD project: We are looking for a highly motivated and talented PhD research
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Cybernetics at NTNU is offering a fully funded PhD position in the area of learning-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks
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Professional qualifications (required) Relevant PhD degree (e.g. computer science, machine learning, statistics) Experience in developing deep learning models for 3D point cloud data Strong programming skills
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epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration
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the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis of the recorded Raman spectra and with biologists on the utility
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proficient in conducting quantitative analyses. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. Alongside
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their research projects, and advising on methodology and academic writing Required selection criteria You must have completed a doctoral degree in (machine learning, statistics, or similar). You must have a