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Field
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machine learning. Strong technical background, including substantial experience with programming in Python and relevant ML/statistics libraries (e.g. PyTorch, Darts, Hugging Face Transformers, Pyro, PyMC
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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++ and Python are required. Experience with control and optimization of power generation systems (e.g., wind power) is desirable but not required. Some experience with real-time control hardware is
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of Washington Labor Relations website: https://hr.uw.edu/labor/about-labor-relations . Duties and Responsibilities Participate in and/or lead research and technology transfer activities, including but not limited
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research area: Python or C#, robotics, additive manufacturing, finite element analysis, or computational fluid dynamics. Experience in teaching and co-supervising thesis students at university level
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maintaining the DataSpaces (https://dataspaces.sci.utah.edu/download/ ) project – a high-performance distributed data management framework designed for in-memory data staging and coordination in scientific
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assessed according to the following weights and criteria: - Quality of the Curriculum - Proven knowledge of imaging data analysis software (20%); proven programming skills: Matlab, Unix, Python (20
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in causal inference ● Minimum of 2 years’ experience in statistical software R, Python or equivalent Preferred Qualifications: ● Experience with development of R packages or other
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(https://atomicfilmslab.org) and will work closely with the computational, device, and simulation teams, as well as with the education and mentorship teams comprising ASWESOME. This position will inform
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& Benefits Orientation for Post-Doctoral Fellows | University of Colorado https://www.cu.edu/employee-services/benefits-wellness/new-employee/pbo/post-doc · benefits guide cover-post-doc-2024 https