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focused on mass spectrometry and development of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and
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SEEC, as well as to coordinate the processing, analysis, and presentation of surveillance data to the research community, stakeholders, and the general public. In addition, the role includes producing
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to help you settle in. Discover more Find more general information about doctoral studies at Chalmers here . Application procedure The application should be written in English be attached as PDF-files, as
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to assimilate knowledge at the research level. Understanding and experience in machine learning and computer vision. Knowledge, experience, and strong interest and in AI and XR development. Knowledge and
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for multiuse purposes, addressing issues on climate change adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities for practical impact by taking the outputs from the developed machine learning
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derivatives to bio-chemicals on the anode side and simultaneously to generate green hydrogen in the cathode side. Subject description Energy engineering concerns the development of technologies and processes in
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or more (with none of the sections scoring less than 5.0) • TOEFL score of 550 or more (computer based test 213, internet based 79) • Cambridge/Oxford - Advanced or Proficiency level. Selection
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score (Academic) of 6.0 or more (with none of the sections scoring less than 5.0) TOEFL score of 550 or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced or Proficiency level