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Pay Range : $26.00 per hour USD Key Responsibilities Include: As a teacher provide a one-to-one teaching experience in the areas of Math, Biology, Chemistry, Physics, Algebra 1, Algebra 2, Geometry, Pre-Calculus, Calculus, and possibly Statistics at grade levels 6-12.
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Grades K-5 Grades 6-8 Algebra 1 Geometry Algebra 2 Pre-Calculus Calculus Statistics. Exceptional math competency through at least Algebra I. Grades K-5 Grades 6-8 Algebra 1 Geometry Algebra 2 Pre-Calculus Calculus Statistics.
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Through your understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory, you will perform data exploration and analysis (look at distributions, find anomalies, create simple visualizations, etc.
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A Research Scientist should possess an M.S. or Ph. D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.
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Ability to operate in mathematical concepts, e.g.: analysis, linear algebra, calculus, statistics and probability. The Group's operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC Rail Services LLC, Manufacturers Bank, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd.
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Mathematics: Knowledge of arithmetic, algebra, geometry, calculus, statistics, and their applications. Familiar with a variety of the aerospace manufacturing field's concepts, practices, and procedures.
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Responsibilities: 75% Teaches no more than 9 credit hours per semester, courses may include mathematical literacy, college algebra, statistics, contemporary mathematics, and co-requisite courses.
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Knowledge of the Mathematics of Machine Learning (particularly Linear Algebra, differential calculus) and Statistics. Masters Degree in Computer Science, Statistics, and/or Math or equivalent, demonstrated through work experience, journal and/or conference publications or open-source projects.
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Solid understanding of (and willing to learn as necessary) topics like signal processing, linear algebra, statistics, machine learning, adaptive filters etc. We are looking for a signal processing or imaging engineer with a strong C/C.
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Strong math skills (e.g. statistics, algebra, calculus) Experience with MLOps tools (Databricks, Airflow, and MLFlow preferred) Experience in machine learning libraries (e.g. TensorFlow, Keras, and PyTorch.
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Deep knowledge of statistics and linear algebra concepts (ANOVA, distributions, PCA) Bachelor's degree (data science, statistics, computer science, or similar preferred). Advanced degree in data science, statistics, computer science, or similar.
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The teaching load will regularly be comprised of courses in mathematics, such as College Algebra, Trigonometry, Calculus I, II and III, and/or Statistics. Additional responsibilities may include possible supervision of internships, participating in curriculum development, training and mentoring adjunct faculty, attending forums and meetings, participating in initiatives related to undergraduate research, grant-writing, and serving on additional department and college committees and boards as requested.
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Practical understanding of the mathematics behind modern machine learning, linear algebra and statistics. You have experience in some of the following domains: Algorithms, Architecture, Artificial Intelligence, Database Systems, Data Mining, Distributed Systems, Machine Learning, Networking, Statistics, Game Theory, Auction Design, or other experience with rigorous Quantitative Analysis or Systems Software implementation.
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Proficient in common geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, AWS Sagemaker, AWS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modeling, TensorFlow, Linear Algebra, R, SAS, NLP.
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Competence with linear algebra, calculus, numerical analysis, and wide range of model estimation techniques a big plus. Masters (or equivalent experience) in computer science, statistics, mathematics, or a related field.
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