63 condition-monitoring-machine-learning Postdoctoral positions at Northeastern University
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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-scale epidemiological datasets using statistical and machine learning methods Conduct systematic literature reviews and meta-analyses on disease dynamics topics Develop and validate predictive models
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to translate rigorous methods into practical tools. QUALIFICATIONS: Ph.D. in Applied Mathematics, Electrical & Computer Engineering, Computer Science, Industrial Engineering, or a closely related field by start
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qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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, policymakers, and advocates. Programming skills are essential (we mostly work in Python, though other languages are welcome), as is a strong grasp of statistics and an eagerness to learn more. Recommended
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receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law. Compensation Grade/Pay Type: 108S Expected Hiring Range
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qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any