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: 281522388 Lecturer D-25-MAT-00004 | Faculty | Mathematics The Mathematics Department at Princeton University seeks to appoint Lecturers to teach courses, sections, and/or do grading in linear algebra
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strong mathematical skills (e.g., probability theory, statistics, calculus, and linear algebra); Have strong communication, presentation and writing skills; Enjoy working in a multidisciplinary research
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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University of California, Los Angeles | Los Angeles, California | United States | about 12 hours ago
. Topics include linear and matrix algebra (with special emphasis on demand/supply and cost/revenue analysis) and differential calculus. Students are encouraged to bring in examples of mathematical
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we favor candidates with previous experience in X-ray imaging preferably for biomedical applications. You should Have a solid grasp of microscopy, electromagnetism/optics and linear algebra Be skilled
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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qualifications Preferred candidates will have experience with programming tools (UNIX, bash, MATLAB/Python programming), a strong college math background (linear algebra) and/or statistics, and previous research
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the Norwegian educational system A solid background in machine learning, mathematics, linear algebra, and/or statistics is also required Solid knowledge and experience in Python programming is required Experience
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programming (e.g., Python) Documented proficiency in deep learning frameworks (e.g., PyTorch) Documented background in machine learning, mathematics, linear algebra, and statistics Fluent oral and written
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candidate will be able to demonstrate the ability to assume a leadership role in teaching and developing applied courses in areas such as math modeling, applied linear algebra, and/or actuarial and data