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our #OneTeam at Fraunhofer ILT! What you will do You will take charge of and work on projects related to additive manufacturing of permeable structures and difficult-to-weld materials Through your
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a highly motivated researcher associate (M/F) with strong background in computational structural biology. The successful candidate will be working on developing AI-based computational approaches
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for experiments using reinforcement learning, Bayesian methods, image analysis and data analysis. Collaborate with interdisciplinary teams, including machine learning experts, device modelling specialist
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
for individuals that are interested in pursuing a PhD in economics or finance. The chosen candidate will also gain valuable experience in the application of machine learning and Bayesian inference methods
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transformative fabrication approaches that enable novel material performance, improved processing pathways, and deployable structural solutions for aerospace, energy, defense, and industrial applications. Key
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multiple affiliations. POSTDOCTORAL ASSOCIATE OPPORTUNITY Acharya Lab – Division of Structural Biology The Acharya Lab in the Division of Structural Biology at the Duke Human Vaccine Institute (DHVI), is
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of candidates will be done according to the final average. Additional comments Examination topics: 1. Structure, morphology, and conformation of polysaccharides. 2. Cellulose: macromolecular structure
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been designed at low Reynolds number, when the flow is mainly populated by small-scale structures. However, as the Reynolds increases, these control strategies become rapidly inefficient