236 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at Technical University of Denmark
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approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see
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by the Danish EUDP project “RePower-HPC.” Future AI and high-performance computing (HPC) systems demand unprecedented power levels driven by massive data processing. A key challenge is enabling
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at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university
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and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment
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for e-DAC. The research will involve molecular-level modeling and data-driven analysis to guide the design of redox-active capture materials, combined with experimental validation in electrochemical cells
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. Development of quantitative image analysis to extract information on atomic vibrations and displacements from image series. Investigate molecular adsorption, surface reconstruction and site-dependent
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. Starting date is 15 April 2026 (or according to mutual agreement). The position is a full-time position. You can read more about career paths at DTU here . Further information Further information may be
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can read more about career paths at DTU here . Further information Further information may be obtained from professor Poul Sørensen, email posq@dtu.dk , mobile phone +45 2136 2766. You can read more
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) Molecular thermodynamics for water Obtaining structural information of water and electrolyte solutions from advanced experimental techniques, including infrared and/or Raman spectroscopy with support from
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against