574 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"IFM" positions at Nature Careers
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workshop for digital and conventional manufacturing (CNC, laser machining, additive manufacturing). At Principal level, you will also contribute to management and long-term technical strategy, infrastructure
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, Süddeutsche Zeitung). Learn more about our research at www.erturk-lab.com . We are seeking a highly motivated AI Scientist (best: Computational Pathologist / Machine Learning Scientist for Digital Pathology) (f
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artificial intelligence, machine learning, and the life sciences to shape the future of data-driven biology and biomedicine. We are seeking visionary researchers whose work pushes the boundaries of AI-enabled
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glycoproteomics, including data analysis Experience in metabolomics, including data analysis Experience in lipidomics, including data analysis Experience with machine learning in proteomics data analysis
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basic science to its effective translation for preventing or alleviating disease. Candidates for this joint appointment should have research interests focused in computational immunology/AI/Machine
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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peripherals). Experience supporting business teams around IT needs. Prefer experience with Windows, Apple, and Linux. Licensure, Registration and/or Certification Required by SJCRH Only: Certification in A
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peripherals). Experience supporting business teams around IT needs. Prefer experience with Windows, Apple, and Linux. Licensure, Registration and/or Certification Required by SJCRH Only: Certification in A
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Professor (W3 / W2 with Tenure Track to W3) for Materials and/or devices for Photonics and Quantum T
quantum technologies. This research can be complemented by digital methods of process simulation and optimization, as well as machine learning. Requirements include an outstanding PhD in materials science
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tabletop, functional, and full-scale drills to test institutional preparedness. Participate in a critique of each drill record lessons learned, and develop improvement plans to address identified shortfalls