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- NTNU Norwegian University of Science and Technology
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- NTNU - Norwegian University of Science and Technology
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- NHH Norwegian School of Economics
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- OsloMet – Oslo Metropolitan University
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synthetic biology, machine learning (ML), and ultrahigh-throughput screening (microfluidics) to discover new enzymes and bioactive molecules with applications in biotechnology, medicine, and sustainability
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, geometric deep learning. Considered an advantage: experience in programming or course work in computer science, algebra, topology or differential geometry, knowledge of topological data analysis or machine
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, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. Duties of the position Fundamental contributions in embodied AI
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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
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, bioinformatics, information security, machine learning, optimization, programming theory, visualization, and didactics. Affiliated centers and labs include the Center for Data Science (CEDAS) , the Computational
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of partial differential equations (PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in
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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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. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier
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Norwegian courses. Required selection criteria You must have completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms
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computer vision models for forest-based 3D point cloud data. In recent years, large advances have been made for deep learning algorithms for high-resolution point clouds from small geographic areas. We seek