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Field
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made significant progress in this direction by merging machine learning interatomic potentials (MLIPs) trained on density functional theory (DFT) data, and enhanced sampling techniques to reach the
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Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians The ELPH-ML project, led by Dr. Ransell D'Souza at the Department of Chemistry and Materials Science, Aalto University, and the Data
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, and international studies—with cutting-edge data science techniques, including Earth Observation (EO) data analysis, machine learning, large-scale collation and analysis of survivor narratives
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technologies, AI and big data. Crop and soil health - resistance and integrated pest management (including AI-driven prediction) and improving the root-soil interface (carbon, water and nutrient availability
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approach towards artificial intelligence that uses the natural dynamic behaviour of physical systems (such as light and electronics) to process information efficiently. You will work at the intersection
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across disciplines An independent, self-motivated approach to research You'll gain skills spanning dynamical systems theory, data science, earthquake science, and soil ecology, working with large, real
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closed‑loop carbon platform suitable for large‑scale deployment. Person Specification Motivation, creativity, and resourcefulness A mature approach to learning Candidates should have been awarded
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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PhD Studentship: Bottom-up Decoding of Protein Conformational Landscapes: from Gas-phase to Solution
folding simulations with mass spectrometry experimental data, creating a unique multi-stranded methodology to map out free energy landscapes associated with protein folding in environments spanning gas
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close interaction with experimental work. About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact HetSys (Centre for Doctoral Training in Modelling of Heterogeneous Systems