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Field
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Job Requirements REQUIRED: PhD in a field of quantitative science; strong background in machine learning and signal processing; experience with and commitment to rigorous and reproducible
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machine learning or chemometric algorithms, LDIR, Py-GCMS and Raman, Caco-2 cells Additional Information Eligibility criteria Mandatory: *PhD in science, chemistry, food engineering or related disciplines
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for the postdoctoral appointment, applicants are required to hold a PhD in electrical engineering or other related subject, or have equivalent qualifications from abroad deemed equivalent to a PhD in electrical
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develop automated workflows integrating artificial intelligence and machine learning (AI/ML) for the Center for Clean Hydrogen’s AEM Moonshot project. The project combines AI/ML, molecular simulation, and
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specific to a single model or setting. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background in machine
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be responsible for designing and implementing physics-informed machine learning strategies for identifying constitutive laws in granular media. This includes the development of thermodynamically
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provide a hands-on STEM learning opportunity focused on Engineering Science. To ensure that our fundamental science and engineering core is vibrant and continually pushing the forefront of knowledge, Sandia
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FAccT and AIES), as well as policy fora. Applicants should have completed, or be near completion of, a PhD in Computer Science, Information Engineering, Statistics, Machine Learning or a closely related
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Technology and Metallurgy, Polymers and Composites, and Sustainable Materials. With some 100 researchers and PhD students and several national and international partners, MSN is emerging as a strong actor in
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theories. The candidate will also be expected to apply these models to predict the engineering behavior of materials in service environments. Position Requirements Recent or soon-to-be-completed PhD