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If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
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Experience with a wide range of AI techniques, including machine learning, deep learning, natural language processing, and computer vision. Advanced degree (PhD or MS) in Computer Science, AI, Machine Learning, or a related field.
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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
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Applicants should possess a PhD in a relevant discipline (computer science, machine learning, epidemiology, electrical engineering, or applied mathematics) and have established an excellent research profile in signal processing or machine learning.
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Scientific software engineering of machine learning potentials for large scale molecular dynamics. Qualifications: Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software (e.g. Quantum Espresso, PySCF, GPAW), fluency with electronic structure theory and quantum chemistry, experience with machine learning regression methods.
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Or MSc in machine learning, data science, computer science, or statistics and substantial experience applying machine learning and data science technologies in a late-stage pharma setting.
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REQUIRED : Ph. D. in civil engineering, urban planning, computer science, operation research, industrial engineering, or a related field by the start of the appointment; experience with transportation systems, spatial and network analysis, optimization, machine learning, statistics, econometrics, large-scale datasets, and cloud computing; record of research that can shape the future of urban transportation and mobility; and strong publication record and communication skills.
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Experience drafting applications related to machine learning, robotics, automotive technologies. Degree in Computer Science, Computer or Software Engineering, Physics, Electrical Engineering, Automotive Engineering or other relevant technical discipline.
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Experience leading teams in data analytics and data visualization, including selecting and applying the appropriate analytical techniques for statistical analysis, predictive modeling, simulation, and machine learning.
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Application domain experience in scientific computing, search, optimization, signal processing, machine learning is a plus. BS, MS, or PhD in Computer Science, Computer Engineering, Mathematics, or Physics.
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About the OpportunityNortheastern University’s Multidisciplinary Graduate Engineering (MGEN) unit seeks highly motivated applicants, committed to teaching excellence, for the role of Assistant/Associate/Full Teaching Professor (a non-Tenure-Track faculty position) in Boston, MA with general areas of focus in Artificial Intelligence, Machine Learning, and Natural Language Processing.
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OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or field related to machine learning/statistics or biology/chemistry.
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An advanced degree (undergraduate, M.S. or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Physics, Data Science, or equivalent quantitative fields such as Engineering, Computer Science with a background in machine learning.
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Experience in machine learning / deep learning, x-ray imaging, medical image reconstruction, or image-guided intervention systems is highly preferred. MS/PhD degree in Computer Science, Electrical Engineering, Biomedical Engineering, Robotics or other related programs.
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The ideal candidate will have a strong background in Software Engineering, and an interest in Computer Vision and/or Machine Learning. New Balance offers a comprehensive traditional benefits package including three options for medical insurance as well as dental, vision, life insurance and 401K. We also proudly offer a slate of more nontraditional perks – opportunities like online learning and development courses, tuition reimbursement, $100 monthly student loan support and various mentorship programs – that encourage our associates to grow personally as they develop professionally.
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machine learning engineering computer jobs in Boston, MA
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