663 machine-learning "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your
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an advantage: plasma surface functionalization; electrode/electrolyte interfaces; battery degradation modelling; microstructure-resolved modelling; tomography or image-based electrode modelling; machine learning
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assigned as needed. The ILS Lab develops innovative methods at the intersection of operations research, artificial intelligence, and machine learning to solve complex supply chain, logistics, and
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Potentials (MLIP), machine learning (ML) predictive models and AI tools. Activities : Computer science implying ML and AI tools applied to material science Where to apply Website https://umontpellier.nous
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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programs. To learn more about UofSC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time-limited positions may be eligible for all, some, or
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
connections between wet and dry lab, bringing together computational biologists building new methods at the interface of structural biology and machine learning and experimentalists studying how proteins