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expertise in robotic state estimation, SLAM, or perception for autonomous systems. A successful candidate should have a strong mathematical background (e.g., linear algebra, optimization, probability
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. The postdoc will engage in research including, but not limited to, the following areas: • Mixed-Integer Linear / Quadratic Programming for large-scale decision-making problem • Non-Convex Optimization and
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. EXPERIENCE: Undergraduate-level experience with statistical analysis (e.g., an upper-division statistics course) or advanced mathematics (e.g., undergraduate level linear algebra) is required. PREFERRED
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the Lie-Størmer Center. The position is associated with the Center’s work package WP4 – Topology, Algebra, and Geometry for Complex Data Analysis. The Lie-Størmer Center is jointly hosted by UiT
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development, e.g., SDN and P4. 3. Must have taken coursework in calculus, linear algebra, probability and statistics, and possess experience in mathematical thinking and abstract reasoning. 4. Willingness
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associated with the Center’s work package WP4 – Topology, Algebra, and Geometry for Complex Data Analysis. The Lie-Størmer Center is jointly hosted by UiT The Arctic University of Norway (UiT) and the
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Complexity» (NewPC). About the project/work tasks The project aims to develop multivariate algorithmic and complexity tools for optimization problems involving geometric and algebraic objects such as points
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complexity tools for optimization problems involving geometric and algebraic objects such as points, vectors, linear spaces, and matrices. Qualifications and personal qualities Applicants must hold a master's
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) Documented background in machine learning, mathematics, linear algebra, and statistics Fluent oral and written communication skills in English Desired qualifications: Experience with transformer models and
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algebraic complexity, with emphasis on GCT, border complexity, Waring/tensor rank, and connections to representation theory and algebraic geometry. Publish research outcomes in leading venues in theoretical