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for working with both public health and/or environmental data/models, and experience working with an interdisciplinary team of researchers and stakeholders. This position is based at the Kansas Geological
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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analysis of cell signalling, this three-years postdoc position at DTU Bioengineering will fulfil your scientific and personal development in an international, multi-disciplinary, and curiosity-driven
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
: PhD in nuclear engineering, applied physics, computational science, or a closely related field; demonstrated experience in Multiphysics modelling, numerical methods for PDEs, and code verification and
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-driven research team. This position will be affiliated with the teams of Associate Professors Chiara Francavilla and Erwin Schoof in the Section for Medical Biotechnology at the Department of Biotechnology
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We invite you to apply for a Postdoctoral Appointee position in the Chemical Sciences and Engineering Division (CSE) at Argonne National Laboratory. This position offers the opportunity
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of reports, dissertations and end-of-study papers. Skills Expertise in the following fields: Chemical and process engineering. Modeling (first-principles and data-driven models), simulation and optimization
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of software engineering techniques to ensure interoperability of their modelling and mining ecosystem. This position will run from October 2025 (or shortly after) and it has an expected duration of 24 months. A
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science applications in engineering. Preferred Experience Academic or professional experience involving interdisciplinary research, including theoretical modeling and experimental validation Experience
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circularity in complex aerospace systems. Via Model Based Systems Engineering (MBSE) we think that it would be possible to successfully predict the effects of proposed design changes on circularity and