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Field
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interdisciplinary and collaborative team of engineers, analysts, and software developers. GAC works to develop and apply state-of-the-art energy system modeling techniques, software, and simulations for breakthrough
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expertise in existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will contribute to building a
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& Applications. The Signal Processing and Communications (SIGCOM) research group of SnT conducts research aimed at designing, emulating and testing new high-performance systems for the future of mobile and
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Fellow will work with the Soil and Plant Testing Laboratory (SPTL) and the Soil Health Assessment Center (SHAC) under the supervision of Dr. Md Rasel Parvej. The position will focus on applied research
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requirements quality assurance and architecture analysis, as well as downstream verification & validation activities, such as software testing and runtime verification. For further information, you may refer to
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(e.g. Docker, Singularity) is desirable. Solid understanding of software development best practices (version control, testing, documentation). Mentoring Skills: Proven ability to mentor and teach others
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physicochemical characterization (SEM, SAXS, DLS, DSC, TGA, DMA, rheology, adhesion testing, FTIR, Raman, XPS) Quantify adhesion, cohesion, rheological, thermal, mechanical properties Establish structure–property
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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, DLS, DSC, TGA, DMA, AFM, rheology, adhesion testing, FTIR, Raman, or comparable methods Evidence of scientific output (e.g., peer-reviewed publications, preprints, patents, software, industrial reports
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. Collaborate with a multidisciplinary team of engineers, computer scientists, and data scientists to put research insights into open-source software products. Publish research findings in leading academic