64 scholarship-phd-agent-based-modelling Postdoctoral positions at Technical University of Denmark
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Engineering of Additive Manufactured Metals—MicroAM’. The MicroAM project aims to develop (i) a laboratory-based X-ray microscope capable of mapping local residual stresses, (ii) a multi-scale AM process
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biobased processes to promote a green transition and support the UN Sustainable Development goals. Responsibilities and qualifications You will work with a team of scientists including PhD and MSc students
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. This position targets a fundamental question: how does the manufacturability of whole-cell-based biosolutions influence their real-world performance in the field? Your research will seek to understand
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. The technologies include fuel cells, electrolysis, power-to-x, batteries, and carbon capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous
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district heating and energy districts based on real-world cases. Our research group brings together experts from diverse backgrounds, with a common focus on improving the efficiency of energy systems
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. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus
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circuits in thin-film lithium niobate (TFLN) [Zhu2021] and tantalate (TFLT) [Powell2024]. Using the ultrafast Pockels effect in TFLN/TFLT, you will build high-speed cavity-based components [Larocque2024
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engineering. It covers a wide range of manufacturing processes and modelling approaches, metrology at all scales, micro/nanomanufacturing, and additive manufacturing. The research is based on a
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-driven analysis and modeling. These are interdisciplinary positions that combine environmental engineering, materials science, and sustainability assessment. We are looking for motivated and forward
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statistical analyses for the tasks. Based on your competence and interests, your tasks will include: Develop and use epidemiological models (for example regression models or SIR-models), including for “what