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at Princeton University seeks to appoint Lecturers to teach courses, sections, and/or do grading in linear algebra, calculus, or upper division math courses. Appointments may be made for one or two semesters
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and coding using either Python or Mathematica are essential. Experience with a computer algebra system such as Mathematica is an advantage. We are also looking for good written and verbal communication
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foundations in linear algebra, calculus, optimization, probability, and statistics for machine learning. Expertise with ML/deep learning frameworks (PyTorch, TensorFlow), libraries (scikit-learn), and
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, applied mathematics, physics, computer science, computational topology, or a related quantitative discipline. A strong foundation in algebraic topology and/or differential geometry (e.g., homology theory
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mechanical engineering, aerospace engineering or a related field. The candidate must have proven experience in numerical simulation in fluid mechanics and/or aeroacoustics; strong background in linear algebra
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candidate must have a proven experience in numerical simulation in fluid mechanics and/or aeroacoustics, as well as strong skills in linear algebra and signal processing. Website for additional job details
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well as strong skills in linear algebra and signal processing. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR3346-NADMAA-158/Default.aspx Work Location(s) Number of offers
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related field. The candidate must demonstrated experience in numerical simulation in fluid mechanics and/or aeroacoustics; strong expertise in linear algebra and signal processing. Website for additional
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PhD in Physics Strong background in quantum mechanics and linear algebra Research experience in quantum information or quantum foundations Publication record in peer-reviewed journals Experience with
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: Required: • MSc (or equivalent) in: Computer Science, Cybersecurity, Machine Learning, or related field • Strong background in: machine learning / deep learning, mathematics (probability, linear algebra