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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
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-learning (ML)- driven and physics-based computational workflows to screen large molecular libraries, predict key electrochemical and physicochemical properties, and deliver ranked shortlists of high[1
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the mandatory PhD research education programme Develop a hybrid numerical and data-driven method to integrate natural design principles into the development of bioinspired materials Perform independent, high
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and computational infrastructure Perform comparative genomic analyses, including phylogenomics Conduct independent research in annelid genomics in close collaboration with project partners Contribute
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industry. Context and motivation The green energy transition is increasingly digital: it relies on turning high-quality (smart meter, grid, or weather) data into actionable insights and better-informed
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relevant Master’s degree in creative or performing arts or documented equivalent competence. Relevant academic backgrounds might be creative music technology, sound art, computer music composition, creative
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required to enable the large-scale use of post-consumer scrap (PCS) aluminium in high-value, structural, and safety-critical products. FAST adopts a through-scale and through-process research methodology
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), at the Norwegian University of Science and Technology (NTNU) has a vacancy for a PhD Candidate. The position is associated with the research project AMAZIEN – Transforming Multifunctional Membranes into High
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risks, improve operational capabilities and ensure functional design that will facilitate long term operation and maintenance with minimum environmental impacts for intakes and outlets, tunnel systems
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