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Lawrence Berkeley National Lab’s ( LBNL ) Applied Mathematics and Computational Research Division has an opening for a Quantum Computing Postdoctoral Fellow to join the team. PhD degree in chemistry, physics, applied mathematics or a relevant field is required.
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Hold a Master’s or Doctorate degree in Physics, Medical Physics, other physical science, engineering, or applied mathematics from an accredited college or university. Utilizing data acquired during the planning process (CT, MRI, PETCT and simulation), generate three dimensional, IMRT, VMAT, SBRT, and/or SRS isodose plans following the specifications of the radiation oncologist.
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Applied R&D expertise in computer science, data science, or applied mathematics in a national security domain. This portfolio includes a mixture of unclassified and classified programs with R&D in vulnerability research, reverse engineering, exploit mitigation techniques, and static and dynamic analyses applied to cyber-physical systems (such as critical infrastructure, IoT, mobile devices, or vehicular systems.
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Education or aptitude for applied mathematics. Familiar with coding taxonomies used in healthcare billing and electronic medical records, such as ICD-10 codes, CPT-4 codes, MS DRGs, SNOMED, LOINC, RxNorm.
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Advanced degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, or a related field. Degree in Statistics, Machine Learning, Computer Science, Applied Mathematics, Operations Research, or a related field.
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Master's degree in: Systems Engineering, Aerospace, Electrical Engineering, Physics, Computer Science, or Applied Mathematics. Bachelor's degree in: Systems Engineering, Aerospace, Computer Science, Applied Mathematics, or another related technical field.
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Preferred Qualifications: Master’s in mathematics, applied mathematics, statistics, computer science, engineering, or a related field with a strong mathematical component Active TS/SCI Proven track record of successful project involvement with government agencies, demonstrating the application of mathematical and computational techniques to address complex challenges in defense or national security domains.
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Foundation in applied mathematics and lumped modelling approach of transient problems. Knowledge of SolidWorks (parametric modelling, assembly, and drafting), metal machining and materials, injection molding and polymer flow/behavior, design for machining and over-molding, finite element analysis (ANSYS Mechanical, CFD, Multiphysics preferred.
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Position Title: Assistant Professor, Chemistry (Regular, Full-Time, Non-Tenure track) Department: Mathematics and Natural Sciences Reports To: Department Chair FLSA: Exempt. Marian University is a Catholic applied liberal arts community that welcomes diverse spiritual traditions.
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Job Summary: The Raytheon (RTX) Data Science and Technologies (DS&T) group performs interdisciplinary applied research and development (R&D) efforts that span fundamental research, concept development, trade studies and rapid prototyping for customized engineering products and services.
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Ph. D. or Master's degree from an accredited university in a quantitative field such as statistics, operations research, quantitative finance, econometrics, applied mathematics, computer science, or engineering.
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Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering.
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BS Degree in Computer Science, Cryptography, Applied Mathematics, or similar domain experience. Leidos in San Diego, CA is looking for a Sr. C Developer to join our team supporting Crypto and Space-Based initiatives.
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Bachelor's degree in a STEM major or with STEM coursework learned in associated majors (Actuarial Science, Computer Science, Data Engineering, Data Science, Mathematics, Applied Mathematics, Statistics, Finance, Economics.
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A master s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 7 years experience in data science or a similar role. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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