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: synthesising and combining results from existing model-based sustainability assessments (e.g. LCA, spatial and scenario analyses) to identify optimal transition pathways and to set out a forward-looking research
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to a platform that supports researchers in understanding and analyzing complex respiratory time-series data. You will merge codebases, implement dedicated data containers, port and optimize signal
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with colleagues in theory who propose optimized designs for your devices, and both receive and provide help to fellow colleagues performing the experiments. You will also have the opportunity to carry out your own
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., proficiency in Python, PyTorch, OpenCV) and experience in deep learning model optimization and familiarity with AI model deployment are required. Candidates with experience in quantitative CT algorithms
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providing innovative composite solutions or optimizing the usage of existing solutions in demanding Energy and Mobility applications. Our laboratory expertise incorporates three main areas: Design of
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process A single curricular phase To validate this request, you must validate the form that is accessed at the URL: https://seleccio.uab.cat Any application that is not submitted in this way will not be
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the applicant and the Department of Ecoscience. The position concludes after 24 months. Job description The Department of Ecoscience, Aarhus University is looking for a post-doctoral researcher to optimize a
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terms of universal computational skills. We encourage you to describe your work using broader technical terms—such as "statistical data analysis," "workflow automation," or "algorithm optimization"—rather
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towards various waste heat recovery strategies to aid in determining which strategy is optimal for given external conditions. Collaborate with Mechanical Engineering faculty, industrial researchers, and
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of the final rankings of the PRIN 2022 call. Where to apply Website https://www.unibg.it/ Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: OTHER Eligibility