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conducted in close collaboration with Everllence (formally known as MAN Energy Solutions). The developed methods have to be tested in simulation and on real engines. Previous Work https://openreview.net/pdf
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 2 months ago
?." arXiv preprint arXiv:1903.03063 (2019). [4] "Modern Random Access for Grant-Free Cellular Networks," C. Adjih, Tutorial, https://indo-french-seminar-6g.github.io/slides/Modern_Random_Access_for_Grant
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Python and/or MATLAB; familiarity with numerical optimization libraries and scientific computing. Strong written and oral communication skills; ability to work independently and in teams. Position Type
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the JAX Python library, including efficient implementations of classical numerical algorithms. 2. Extend the hybrid FEA-ML framework to include nonlinear cohesive zone models with simple traction separation
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the JAX Python library, including efficient implementations of classical numerical algorithms. 2. Extend the hybrid FEA-ML framework to include nonlinear cohesive zone models with simple traction separation
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quality (PM2.5, CO2, Nox, etc.) and energy monitoring (voltages, currents, battery charge/discharge cycles); Proficiency in languages commonly used in IoT, such as C/C++, Python, and JavaScript. Expertise
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), National Animal Disease Center, Virus and Prion Research Unit, located in Ames, Iowa. For an introduction to the flu-crew at the National Animal Disease Center, please see: https://youtu.be/kOJy8tFTuiI
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or Departmental Website: https://med.stanford.edu/michellelinlab.html (link is external) How to Submit Application Materials: Please send materials to PI Dr. Michelle Lin (mplin [at] stanford.edu) with the subject
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. Programming experience, preferably in Python or R, and experience in the Linux environment Solid publication record in peer-reviewed journals. Proficient in verbal and written English. Excellent teamwork
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skills in quantitative data collection, management, and statistical analysis Excellent coding and programming skills (e.g., Python, R, Stata) Strong interest in research in the fields of sustainability