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sustainable machine learning approaches and addressing renewable energy related projects. Likewise, deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research. PhD
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Job Description This PhD position focuses on fundamental and applied research in electrochemical direct air capture (e-DAC) at DTU Energy. The project addresses key scientific and technological
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. To do so, you will combine atomistic simulations (density functional theory and ab-initio molecular dynamics simulations) with new machine learning models to parameterize machine learning force fields
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career paths at DTU here . Further information Further information may be obtained from Carsten Baum (e-mail: cabau@dtu.dk , website: www.carstenbaum.com ). You can read more about DTU Compute
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study programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations
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information Further information may be obtained from Luisa Siniscalchi (e-mail: luisi@dtu.dk, website: www.luisasiniscalchi.com/) You can read more about DTU Compute at www.compute.dtu.dk . If you are applying
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Dynamics, Bioprocess engineering, Data Science, Machine Learning, Computational Chemistry Offer Description MSCA Doctoral Network machinE LEarning for inteGrated and multi-parAmetric eNzyme and bioproCess
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning