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and recovery. Use advanced analytical techniques to identify reaction products and guide process optimization. Collaborate with modelling, reactor engineering, and sustainability experts across the
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Health and Optimization Methods, which will enhance the university’s national footprint in digital health and optimization methods. This position will help support interdisciplinary collaborations in
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-scale infrastructure systems. For more details, see https://research.chalmers.se/en/project/12873 Who we are looking for The following requirements are mandatory: A doctoral degree in applied
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real-time, sustainability-focused operations. The PhD project should include predictive models and optimization frameworks to guide the shipping sector’s transition. Moreover, the PhD student is
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each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself. You find information about the recruitment process at: https://employment.ku.dk
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centerized control of all on-board power electronics devices. The integration of power electronics enables optimization of the system design and harmonization of different functionalities for reliable
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optimization. Sustainability assessment, circular construction and lifecycle thinking. Technology implementation and organizational change. Data-driven decision making and evidence-based improvement of
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, Electrical engineering, or equivalent. You will need strong written and verbal communication skills in English. Strong machine learning fundamentals (probability, statistics, optimization) and strong
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components will guide the design optimization. The doctoral students will be partly involved in other research activities that contribute to the training purpose. Who we are looking for The following
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theory in a variety of subfields of statistics relevant to AI-enabled experimentation, including: experimental design, clinical trial design, and sequential experimentation Bayesian optimization and